Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana The Implementation team is focused on integrating Altana's products with customers to provide unique insights, business process integrations, and create mutual value. We execute complex customer integrations to create and customize data pipelines for unique customer scenarios; integrate proprietary customer data to our knowledge graph while preserving privacy. The Implementation team works closely with customers, as well as our internal engineering, machine learning, and product organizations. Specifically, the team is focussed on: Develop, deploy and continuously improve distributed, big-data pipelines powering Altana's state of the art network analysis, ML, data ingestion and fusion capabilities Understanding and driving forward Altana's technology to make it more scalable and to meet the evolving requirements of our customer base Serve as the technical expert in client-facing meetings, bridging the gap between complex government requirements and our platform's technical architecture. Work in a cross-functional team of engineers, data scientists, and product managers Evaluate and recommend new tools, technologies, and best practices for data pipeline development, orchestration and deployment About You You are a data engineer with a strong technical background who excels at building trust and communicating complex technical concepts to stakeholders. You are someone who proactively takes ownership of the end-to-end design and operation of data solutions and refines the systems to deliver measurable results. You will have worked across design, development, and maintenance of data models from a variety of sources and schemas Experience across the full lifecycle (Design, Development, Test, Deploy, Monitor, Maintain) of data ingestion and standardization pipelines. A demonstrated drive for sustainable software development, self-healing data workflows, and a deep appreciation for data security and data governance. Excellent written and verbal communication skills, with a track record of successfully interacting directly with external customers and stakeholders to scope technical work and manage expectations. You are eligible and willing to obtain UK Security Check (SC) clearance or have an active clearance already 5 years+ technical experience in data engineering or closely related roles Keep up to date with latest trends in data engineering and care deeply about engineering excellence and knowledge sharing Nice to have, but not required Expertise or experience with the deployment of ML pipelines. Exposure to trade compliance, supply chain management or a field similarly related to international commerce. Experience working with or within public sector. Experience with the responsibilities involved in managing a data platform, including monitoring and managing releases, costs, and infrastructure changes. Familiarity using AI tools to enhance the quality & pace of your output. Technologies we love Languages: Python, Spark, SQL Tools: AWS, Azure, Git, Rest APIs, Kubernetes, Docker Datastores: Databricks, OpenSearch, Postgres Why it's great to work at Altana We love to collaborate, and we win as a team! We are committed to engineering excellence We value personal and professional development We learn from diverse backgrounds and perspectives We impact the world, from enabling developing countries to identifying drug traffickers At Altana, we believe that a diverse workforce enables greater creativity, performance, and adaptability. We're proud to be an equal opportunity employer and welcome you to join us as you are. Our employment opportunities and decisions are based on business needs and individual qualifications, without regard to race, color, religious creed, national origin, ancestry, age, physical or mental disability, medical condition, marital status, sexual orientation, gender identity or expression, genetic information, family care or medical leave status, military or veteran status, or any other characteristic protected by the laws or regulations in the areas in which we operate. We prohibit discrimination and harassment of any type, in any situation. Offers related to employment at Altana will come from an Altana.ai email address. We will never ask for payment as part of the interview or onboarding process.
09/06/2026
Full time
Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana The Implementation team is focused on integrating Altana's products with customers to provide unique insights, business process integrations, and create mutual value. We execute complex customer integrations to create and customize data pipelines for unique customer scenarios; integrate proprietary customer data to our knowledge graph while preserving privacy. The Implementation team works closely with customers, as well as our internal engineering, machine learning, and product organizations. Specifically, the team is focussed on: Develop, deploy and continuously improve distributed, big-data pipelines powering Altana's state of the art network analysis, ML, data ingestion and fusion capabilities Understanding and driving forward Altana's technology to make it more scalable and to meet the evolving requirements of our customer base Serve as the technical expert in client-facing meetings, bridging the gap between complex government requirements and our platform's technical architecture. Work in a cross-functional team of engineers, data scientists, and product managers Evaluate and recommend new tools, technologies, and best practices for data pipeline development, orchestration and deployment About You You are a data engineer with a strong technical background who excels at building trust and communicating complex technical concepts to stakeholders. You are someone who proactively takes ownership of the end-to-end design and operation of data solutions and refines the systems to deliver measurable results. You will have worked across design, development, and maintenance of data models from a variety of sources and schemas Experience across the full lifecycle (Design, Development, Test, Deploy, Monitor, Maintain) of data ingestion and standardization pipelines. A demonstrated drive for sustainable software development, self-healing data workflows, and a deep appreciation for data security and data governance. Excellent written and verbal communication skills, with a track record of successfully interacting directly with external customers and stakeholders to scope technical work and manage expectations. You are eligible and willing to obtain UK Security Check (SC) clearance or have an active clearance already 5 years+ technical experience in data engineering or closely related roles Keep up to date with latest trends in data engineering and care deeply about engineering excellence and knowledge sharing Nice to have, but not required Expertise or experience with the deployment of ML pipelines. Exposure to trade compliance, supply chain management or a field similarly related to international commerce. Experience working with or within public sector. Experience with the responsibilities involved in managing a data platform, including monitoring and managing releases, costs, and infrastructure changes. Familiarity using AI tools to enhance the quality & pace of your output. Technologies we love Languages: Python, Spark, SQL Tools: AWS, Azure, Git, Rest APIs, Kubernetes, Docker Datastores: Databricks, OpenSearch, Postgres Why it's great to work at Altana We love to collaborate, and we win as a team! We are committed to engineering excellence We value personal and professional development We learn from diverse backgrounds and perspectives We impact the world, from enabling developing countries to identifying drug traffickers At Altana, we believe that a diverse workforce enables greater creativity, performance, and adaptability. We're proud to be an equal opportunity employer and welcome you to join us as you are. Our employment opportunities and decisions are based on business needs and individual qualifications, without regard to race, color, religious creed, national origin, ancestry, age, physical or mental disability, medical condition, marital status, sexual orientation, gender identity or expression, genetic information, family care or medical leave status, military or veteran status, or any other characteristic protected by the laws or regulations in the areas in which we operate. We prohibit discrimination and harassment of any type, in any situation. Offers related to employment at Altana will come from an Altana.ai email address. We will never ask for payment as part of the interview or onboarding process.
We are seeking an experienced and adaptable machine learning (ML) and artificial intelligence (AI) engineering professional to join a nimble and best in class data team at The Beatport Group. The role will report to the Director of Intelligence Engineering and will share in the ownership and delivery of cutting edge, scalable ML/AI models. Initial Workstreams Recommendations and personalization Search optimization Audio modeling As a Senior ML & AI Engineer, you will be responsible for: Developing and implementing ML and AI based solutions to enhance and optimize the Beatport customer experience, including semantic search, content recommendation/personalization engines, and audio models for music professionals. Acting as a subject matter expert regarding GCP's latest ML/AI tooling and continuously prototyping and advocating for new tooling. Owning the development cycle of our ML and AI pipelines, ensuring low latency, cost effectiveness, robust CI/CD, and continuous iterative testing. Collaborating with Platform Engineering and Product to prioritize relevant workstreams across the Beatport Group. Working with data scientists, data engineers, and data analysts to refine and develop scalable data architectures to deliver unified and actionable ML/AI intelligence across the data stack. Requirements 4-5 years of direct experience as an ML/AI focused engineer, with 1+ year in a senior capacity preferred. Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field. Expert proficiency in GCP's ML/AI tooling, its data ecosystem, and Python with core ML/AI libraries (PyTorch, XGBoost, TensorFlow). Expert proficiency with SQL development, with Google dialects being advantageous. Proficiency with an API web framework (FastAPI, Django, Flask). Robust CI/CD discipline for ML, including GitHub Actions or GitLab CI, and infrastructure as code solutions such as Terraform. Desired Experience Experience in a data science or adjacent environment. Familiarity with experimentation and A/B testing frameworks. Experience with vector databases or similar technologies for semantic search and retrieval pipelines. Experience with dbt. Domain knowledge in digital signal processing and/or audio fingerprinting within the music industry. General music industry experience or interest in DJ culture. Location Hybrid (London) or remote (UK) - must have right to work in the UK. Benefits Participation in company's annual bonus pool program Professional environment with room for creativity and fun VIP access to local music events & livestreams Enhanced holiday allowance Focus days BUPA Health Insurance Learning days Employer matched pension + More Equal Employment Opportunity The Beatport Group strongly supports equal employment opportunity for all applicants regardless of race, color, religion, sex, gender identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, sexual orientation, genetic information, or any other characteristic protected by state or federal law.
09/06/2026
Full time
We are seeking an experienced and adaptable machine learning (ML) and artificial intelligence (AI) engineering professional to join a nimble and best in class data team at The Beatport Group. The role will report to the Director of Intelligence Engineering and will share in the ownership and delivery of cutting edge, scalable ML/AI models. Initial Workstreams Recommendations and personalization Search optimization Audio modeling As a Senior ML & AI Engineer, you will be responsible for: Developing and implementing ML and AI based solutions to enhance and optimize the Beatport customer experience, including semantic search, content recommendation/personalization engines, and audio models for music professionals. Acting as a subject matter expert regarding GCP's latest ML/AI tooling and continuously prototyping and advocating for new tooling. Owning the development cycle of our ML and AI pipelines, ensuring low latency, cost effectiveness, robust CI/CD, and continuous iterative testing. Collaborating with Platform Engineering and Product to prioritize relevant workstreams across the Beatport Group. Working with data scientists, data engineers, and data analysts to refine and develop scalable data architectures to deliver unified and actionable ML/AI intelligence across the data stack. Requirements 4-5 years of direct experience as an ML/AI focused engineer, with 1+ year in a senior capacity preferred. Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field. Expert proficiency in GCP's ML/AI tooling, its data ecosystem, and Python with core ML/AI libraries (PyTorch, XGBoost, TensorFlow). Expert proficiency with SQL development, with Google dialects being advantageous. Proficiency with an API web framework (FastAPI, Django, Flask). Robust CI/CD discipline for ML, including GitHub Actions or GitLab CI, and infrastructure as code solutions such as Terraform. Desired Experience Experience in a data science or adjacent environment. Familiarity with experimentation and A/B testing frameworks. Experience with vector databases or similar technologies for semantic search and retrieval pipelines. Experience with dbt. Domain knowledge in digital signal processing and/or audio fingerprinting within the music industry. General music industry experience or interest in DJ culture. Location Hybrid (London) or remote (UK) - must have right to work in the UK. Benefits Participation in company's annual bonus pool program Professional environment with room for creativity and fun VIP access to local music events & livestreams Enhanced holiday allowance Focus days BUPA Health Insurance Learning days Employer matched pension + More Equal Employment Opportunity The Beatport Group strongly supports equal employment opportunity for all applicants regardless of race, color, religion, sex, gender identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, sexual orientation, genetic information, or any other characteristic protected by state or federal law.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) caf s or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
08/06/2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) caf s or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. We're proud to be a Living Wage accredited Employer. What You'll Do: The Monolith AI Platform Engineering Team at CoreWeave is responsible for building and scaling the data and workflow backbone that powers the world's most advanced engineering simulation and AI workflows - our ambition is to become the super intelligent AI test lab for the engineering industry, helping customers ship science, faster. From high throughput data ingestion and feature pipelines to model training and real time inference, our platform delivers the performant, reliable, and trustworthy data foundation trusted by the world's largest engineering companies. The Staff Data Engineer will own and evolve Monolith's platform data services and ETL offerings - the data onboarding, preparation, and lineage capabilities that turn fragmented, real world engineering data into production ready training and inference pipelines. You'll partner with Product, Engineering, and Customer facing teams to deeply understand client data challenges and translate them into scalable, self serve data platform features. About the Role: We're seeking a Staff Data Engineer who can own Monolith's data platform surface end to end: from offline batch pipelines and large historical backfills to low latency, real time streaming data flows that power online inference and feedback loops. You'll define and drive our data architecture, champion data quality and lineage, and decide how customer data moves through Monolith from raw ingestion to governed, observable, and reproducible training sets. You'll primarily work with internal teams (Product, Customer Success, Forward Deployed Engineers, Software Engineers, Data Scientists), and step in as a domain expert when clients need deeper guidance. In this role, you will: Own Monolith's Data Platform & ETL Surface Lead the architecture and evolution of core data services for ingestion, transformation, validation, and lineage across training and inference workloads. Design and maintain end to end data models and schemas that make complex engineering, simulation, and telemetry data discoverable, reusable, and performant. Define standards, contracts, and APIs for how product teams and integrations interact with data services. Design & Operate Batch + Streaming Pipelines Build and operate batch pipelines for large scale historical imports, retraining data sets, and migrations from legacy environments. Design and implement streaming pipelines (e.g., using Kafka or similar technologies) for event driven or real time ingestion and transformation that support online inference, monitoring, and feedback loops. Select and integrate off the shelf, industry proven ETL / ELT technologies and own their rollout and long term operation. Champion Data Lineage, Governance & DataOps Implement and maintain end to end data lineage from source systems to derived features and model artifacts, enabling reproducibility, compliance, and faster debugging. Establish DataOps practices: CI/CD for pipelines, observability (metrics, logs, traces), and operational runbooks for data incidents. Help define data quality and governance standards in partnership with Security, Compliance, and Customer Success, including support for privacy and regulatory needs. Partner Across Monolith & CoreWeave Work with Monolith product and engineering teams to expose data services that unlock new user workflows and AI capabilities. Collaborate with CoreWeave infrastructure and AI platform teams to leverage storage, compute, and observability for reliable data flows. Serve as a technical escalation point for forward deployed and customer facing engineers when questions go deeper than playbooks. Who You Are: Experience & Level 8+ years as a Data Engineer / Data Platform Engineer (or similar), owning production data pipelines and architectural decisions. Staff level impact: leading critical data domains and cross team initiatives. Data Engineering & Architecture Deep experience designing end to end data architectures covering ingestion, storage, transformation, serving, and observability. Hands on experience with both batch and streaming pipelines: batch (historical backfills, retraining) and streaming (Kafka or similar, low latency consumption). Proficiency with SQL and at least one major analytical database or data warehouse (PostgreSQL or similar), including schema design and performance tuning. Proficiency with Spark or Ray or similar distributed data processing frameworks. Solid understanding of data modeling (event logs, star schemas, feature tables) in multi tenant SaaS or platform contexts. Tooling & Ecosystem Hands on with data orchestration and ETL tooling (Airflow, dbt, Dagster, Temporal, or equivalents) and able to evaluate and recommend tools that fit our needs. Experience integrating and operating off the shelf data infrastructure, including rollout, migration plans, and ongoing ownership. Familiarity with cloud infrastructure and containerization (Docker, Kubernetes, at least one major cloud provider) for deploying and scaling data workloads. Data Lineage, Quality & DataOps Extensive experience implementing data lineage solutions for debugging, compliance, and auditability. Strong background in data quality: validation frameworks, monitoring, and guardrails that prevent bad data downstream. Proficiency with DevOps / DataOps practices: infra as code, CI/CD for pipelines, runbooks, on call incident response for data issues. Programming, Systems & Communication Strong programming skills in Python for building data services, transformations, and platform integrations. Comfortable working in service oriented architectures, reasoning about data contracts, SLAs, and failure modes across services. Clear written and verbal communicator able to explain data architectures and trade offs to internal stakeholders and occasionally client conversations. Preferred Experience in ML/AI platforms or MLOps environments where data pipelines feed experimentation, training, and inference workflows at scale. Background with time series, simulation, or experimental data (physical test benches, sensors, engineering simulations). Familiarity with feature stores, experiment tracking systems, or model registries and their integration with upstream pipelines. Experience designing data systems for regulated or safety critical domains, including privacy, residency, and retention considerations. What We Offer Family level Medical Insurance Family level Dental Insurance Generous Pension Contribution Life Assurance at 4x Salary Critical Illness Cover Employee Assistance Programme Tuition Reimbursement Work culture focused on innovative disruption Our Workplace While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration. CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. To fulfil our obligation to protect client data, successful applicants offered employment with CoreWeave will be required to complete a basic criminal record check, conducted in compliance with GDPR. Employment offers are conditional upon receiving satisfactory check results.
08/06/2026
Full time
CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. We're proud to be a Living Wage accredited Employer. What You'll Do: The Monolith AI Platform Engineering Team at CoreWeave is responsible for building and scaling the data and workflow backbone that powers the world's most advanced engineering simulation and AI workflows - our ambition is to become the super intelligent AI test lab for the engineering industry, helping customers ship science, faster. From high throughput data ingestion and feature pipelines to model training and real time inference, our platform delivers the performant, reliable, and trustworthy data foundation trusted by the world's largest engineering companies. The Staff Data Engineer will own and evolve Monolith's platform data services and ETL offerings - the data onboarding, preparation, and lineage capabilities that turn fragmented, real world engineering data into production ready training and inference pipelines. You'll partner with Product, Engineering, and Customer facing teams to deeply understand client data challenges and translate them into scalable, self serve data platform features. About the Role: We're seeking a Staff Data Engineer who can own Monolith's data platform surface end to end: from offline batch pipelines and large historical backfills to low latency, real time streaming data flows that power online inference and feedback loops. You'll define and drive our data architecture, champion data quality and lineage, and decide how customer data moves through Monolith from raw ingestion to governed, observable, and reproducible training sets. You'll primarily work with internal teams (Product, Customer Success, Forward Deployed Engineers, Software Engineers, Data Scientists), and step in as a domain expert when clients need deeper guidance. In this role, you will: Own Monolith's Data Platform & ETL Surface Lead the architecture and evolution of core data services for ingestion, transformation, validation, and lineage across training and inference workloads. Design and maintain end to end data models and schemas that make complex engineering, simulation, and telemetry data discoverable, reusable, and performant. Define standards, contracts, and APIs for how product teams and integrations interact with data services. Design & Operate Batch + Streaming Pipelines Build and operate batch pipelines for large scale historical imports, retraining data sets, and migrations from legacy environments. Design and implement streaming pipelines (e.g., using Kafka or similar technologies) for event driven or real time ingestion and transformation that support online inference, monitoring, and feedback loops. Select and integrate off the shelf, industry proven ETL / ELT technologies and own their rollout and long term operation. Champion Data Lineage, Governance & DataOps Implement and maintain end to end data lineage from source systems to derived features and model artifacts, enabling reproducibility, compliance, and faster debugging. Establish DataOps practices: CI/CD for pipelines, observability (metrics, logs, traces), and operational runbooks for data incidents. Help define data quality and governance standards in partnership with Security, Compliance, and Customer Success, including support for privacy and regulatory needs. Partner Across Monolith & CoreWeave Work with Monolith product and engineering teams to expose data services that unlock new user workflows and AI capabilities. Collaborate with CoreWeave infrastructure and AI platform teams to leverage storage, compute, and observability for reliable data flows. Serve as a technical escalation point for forward deployed and customer facing engineers when questions go deeper than playbooks. Who You Are: Experience & Level 8+ years as a Data Engineer / Data Platform Engineer (or similar), owning production data pipelines and architectural decisions. Staff level impact: leading critical data domains and cross team initiatives. Data Engineering & Architecture Deep experience designing end to end data architectures covering ingestion, storage, transformation, serving, and observability. Hands on experience with both batch and streaming pipelines: batch (historical backfills, retraining) and streaming (Kafka or similar, low latency consumption). Proficiency with SQL and at least one major analytical database or data warehouse (PostgreSQL or similar), including schema design and performance tuning. Proficiency with Spark or Ray or similar distributed data processing frameworks. Solid understanding of data modeling (event logs, star schemas, feature tables) in multi tenant SaaS or platform contexts. Tooling & Ecosystem Hands on with data orchestration and ETL tooling (Airflow, dbt, Dagster, Temporal, or equivalents) and able to evaluate and recommend tools that fit our needs. Experience integrating and operating off the shelf data infrastructure, including rollout, migration plans, and ongoing ownership. Familiarity with cloud infrastructure and containerization (Docker, Kubernetes, at least one major cloud provider) for deploying and scaling data workloads. Data Lineage, Quality & DataOps Extensive experience implementing data lineage solutions for debugging, compliance, and auditability. Strong background in data quality: validation frameworks, monitoring, and guardrails that prevent bad data downstream. Proficiency with DevOps / DataOps practices: infra as code, CI/CD for pipelines, runbooks, on call incident response for data issues. Programming, Systems & Communication Strong programming skills in Python for building data services, transformations, and platform integrations. Comfortable working in service oriented architectures, reasoning about data contracts, SLAs, and failure modes across services. Clear written and verbal communicator able to explain data architectures and trade offs to internal stakeholders and occasionally client conversations. Preferred Experience in ML/AI platforms or MLOps environments where data pipelines feed experimentation, training, and inference workflows at scale. Background with time series, simulation, or experimental data (physical test benches, sensors, engineering simulations). Familiarity with feature stores, experiment tracking systems, or model registries and their integration with upstream pipelines. Experience designing data systems for regulated or safety critical domains, including privacy, residency, and retention considerations. What We Offer Family level Medical Insurance Family level Dental Insurance Generous Pension Contribution Life Assurance at 4x Salary Critical Illness Cover Employee Assistance Programme Tuition Reimbursement Work culture focused on innovative disruption Our Workplace While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration. CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. To fulfil our obligation to protect client data, successful applicants offered employment with CoreWeave will be required to complete a basic criminal record check, conducted in compliance with GDPR. Employment offers are conditional upon receiving satisfactory check results.
About Faculty At Faculty, we transform organisational performance through safe, impactful and human centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you'll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world. About the Role We're actively seeking skilled engineers to develop our cutting edge product, Frontier. Working within the core Platform, this role will require a mix of backend services and cloud infrastructure related work to develop Frontier - our next generation Decision Intelligence AI platform. As we continue to expand our platform's reach, you'll have the unique opportunity to build a scalable AI focused product, whilst leading the way in best technical practices. In this role, you'll be immersed in hands on work, tackling complex real world challenges using state of the art technology. From optimising multinational supply chain logistics to reducing time to market for clinical trials and supporting sustainability goals in various industries, Frontier empowers organisations to make informed decisions through AI driven insights. Join us on this exciting journey of transforming decision making with AI and machine learning, revolutionising how businesses thrive utilising Decision Intelligence. What you will be doing: Collaborating with other Engineers in the team, developing and implementing AI driven software solutions built on a modern, cloud native architecture. Helping define and develop the architecture for the team's deliverables. Engaging in code reviews & pair programming with other engineers, directly impacting customer projects and outcomes. Working in an Agile environment with cross functional teams, including data scientists, project managers, and business stakeholders, to understand customer needs and translate them into technical requirements. What we are looking for: We're seeking a candidate with the following qualifications: Strong mathematical mindset Proficiency in Python, and its use in building modern web applications using frameworks such as FastAPI or Flask. Familiarity with at least one Infrastructure as Code platform (Terraform/CDK, CloudFormation). Experience with PostgreSQL, MySQL or other similar relational database technologies. Experience with Data Warehousing is considered a plus. Knowledge of modern CI/CD pipelines (GitLab, GitHub or equivalent). Strong understanding of system architecture and design. Experience deploying enterprise applications on the cloud. Experience collaborating with Product Managers to ensure delightful customer experiences. Expertise in Docker with deployment on Kubernetes preferred What we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You'll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you'll learn something new from everyone you meet.
08/06/2026
Full time
About Faculty At Faculty, we transform organisational performance through safe, impactful and human centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you'll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world. About the Role We're actively seeking skilled engineers to develop our cutting edge product, Frontier. Working within the core Platform, this role will require a mix of backend services and cloud infrastructure related work to develop Frontier - our next generation Decision Intelligence AI platform. As we continue to expand our platform's reach, you'll have the unique opportunity to build a scalable AI focused product, whilst leading the way in best technical practices. In this role, you'll be immersed in hands on work, tackling complex real world challenges using state of the art technology. From optimising multinational supply chain logistics to reducing time to market for clinical trials and supporting sustainability goals in various industries, Frontier empowers organisations to make informed decisions through AI driven insights. Join us on this exciting journey of transforming decision making with AI and machine learning, revolutionising how businesses thrive utilising Decision Intelligence. What you will be doing: Collaborating with other Engineers in the team, developing and implementing AI driven software solutions built on a modern, cloud native architecture. Helping define and develop the architecture for the team's deliverables. Engaging in code reviews & pair programming with other engineers, directly impacting customer projects and outcomes. Working in an Agile environment with cross functional teams, including data scientists, project managers, and business stakeholders, to understand customer needs and translate them into technical requirements. What we are looking for: We're seeking a candidate with the following qualifications: Strong mathematical mindset Proficiency in Python, and its use in building modern web applications using frameworks such as FastAPI or Flask. Familiarity with at least one Infrastructure as Code platform (Terraform/CDK, CloudFormation). Experience with PostgreSQL, MySQL or other similar relational database technologies. Experience with Data Warehousing is considered a plus. Knowledge of modern CI/CD pipelines (GitLab, GitHub or equivalent). Strong understanding of system architecture and design. Experience deploying enterprise applications on the cloud. Experience collaborating with Product Managers to ensure delightful customer experiences. Expertise in Docker with deployment on Kubernetes preferred What we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You'll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you'll learn something new from everyone you meet.
AI Engineer Role Overview The AI Engineer is responsible for developing, deploying and supporting production grade AI and generative AI solutions across JD Group. Reporting into the Head of Data Science & AI, the role focuses on hands on engineering delivery of AI systems, including LLM based applications, retrieval augmented generation pipelines and supporting AI services. Working closely with Senior AI Engineers, Senior Data Scientists, Data Engineering, Platform and Product teams, the AI Engineer contributes to the build and operation of scalable, secure and cost effective AI solutions embedded into core business processes. This role sits between Junior and Senior AI Engineer, with increasing accountability for solution delivery, production readiness and technical decision making within defined problem areas. Responsibilities AI Solution Development Design, build and support AI and GenAI solutions under the guidance of Senior AI Engineers Develop LLM based applications, RAG pipelines and AI services using established architectures and patterns Implement inference pipelines, APIs and microservices to support AI driven use cases Contribute to technical decisions within defined components or services Production Readiness, LLMOps & MLOps Support deployment of AI systems into production environments Implement monitoring, logging and basic observability for AI services Ensure code, configurations and pipelines are version controlled, tested and documented Follow established LLMOps, MLOps and CI/CD standards and practices Assist with performance optimisation, cost management and reliability improvements Governance, Risk & Responsible AI Build AI systems in line with responsible AI principles, security and data protection requirements Support model evaluation, testing and quality assurance activities Ensure AI services comply with agreed governance, auditability and risk controls Collaboration & Stakeholder Engagement Work closely with Senior Data Scientists to support productionisation of AI driven analytical and decisioning solutions Collaborate with Data Engineering, Platform and DevOps teams as part of delivery squads Communicate technical concepts, progress and risks clearly within the delivery team Support Product and Engineering teams in integrating AI capabilities into applications and workflows Learning & Capability Development Continuously develop skills in AI engineering, generative AI, cloud platforms and modern engineering practices Learn from Senior AI Engineers through design reviews, code reviews and delivery feedback Contribute to shared components, documentation and reusable assets as capability grows Stay informed on developments in AI tooling and platforms, applying learning where appropriate Role Objectives & KPIs Deliver high quality AI engineering outputs that support production AI solutions Successful contribution to end to end delivery of AI initiatives Reliability, performance and maintainability of AI services owned Adherence to engineering, security and governance standards Positive feedback from Senior AI Engineers and delivery stakeholders Demonstrated progression in technical capability, autonomy and delivery ownership Skills and Experience 2-3 years experience in AI Engineering, ML Engineering or Software Engineering roles Practical experience building and supporting AI or ML driven applications Good Python skills and experience developing backend services or pipelines Understanding of LLMs, generative AI concepts and RAG patterns Experience working with cloud platforms, with GCP preferred Familiarity with CI/CD, version control and modern engineering practices Ability to work collaboratively in cross functional teams Experience in large scale, multi brand, or global enterprises; retail experience is advantageous Curious, delivery focused and keen to learn
08/06/2026
Full time
AI Engineer Role Overview The AI Engineer is responsible for developing, deploying and supporting production grade AI and generative AI solutions across JD Group. Reporting into the Head of Data Science & AI, the role focuses on hands on engineering delivery of AI systems, including LLM based applications, retrieval augmented generation pipelines and supporting AI services. Working closely with Senior AI Engineers, Senior Data Scientists, Data Engineering, Platform and Product teams, the AI Engineer contributes to the build and operation of scalable, secure and cost effective AI solutions embedded into core business processes. This role sits between Junior and Senior AI Engineer, with increasing accountability for solution delivery, production readiness and technical decision making within defined problem areas. Responsibilities AI Solution Development Design, build and support AI and GenAI solutions under the guidance of Senior AI Engineers Develop LLM based applications, RAG pipelines and AI services using established architectures and patterns Implement inference pipelines, APIs and microservices to support AI driven use cases Contribute to technical decisions within defined components or services Production Readiness, LLMOps & MLOps Support deployment of AI systems into production environments Implement monitoring, logging and basic observability for AI services Ensure code, configurations and pipelines are version controlled, tested and documented Follow established LLMOps, MLOps and CI/CD standards and practices Assist with performance optimisation, cost management and reliability improvements Governance, Risk & Responsible AI Build AI systems in line with responsible AI principles, security and data protection requirements Support model evaluation, testing and quality assurance activities Ensure AI services comply with agreed governance, auditability and risk controls Collaboration & Stakeholder Engagement Work closely with Senior Data Scientists to support productionisation of AI driven analytical and decisioning solutions Collaborate with Data Engineering, Platform and DevOps teams as part of delivery squads Communicate technical concepts, progress and risks clearly within the delivery team Support Product and Engineering teams in integrating AI capabilities into applications and workflows Learning & Capability Development Continuously develop skills in AI engineering, generative AI, cloud platforms and modern engineering practices Learn from Senior AI Engineers through design reviews, code reviews and delivery feedback Contribute to shared components, documentation and reusable assets as capability grows Stay informed on developments in AI tooling and platforms, applying learning where appropriate Role Objectives & KPIs Deliver high quality AI engineering outputs that support production AI solutions Successful contribution to end to end delivery of AI initiatives Reliability, performance and maintainability of AI services owned Adherence to engineering, security and governance standards Positive feedback from Senior AI Engineers and delivery stakeholders Demonstrated progression in technical capability, autonomy and delivery ownership Skills and Experience 2-3 years experience in AI Engineering, ML Engineering or Software Engineering roles Practical experience building and supporting AI or ML driven applications Good Python skills and experience developing backend services or pipelines Understanding of LLMs, generative AI concepts and RAG patterns Experience working with cloud platforms, with GCP preferred Familiarity with CI/CD, version control and modern engineering practices Ability to work collaboratively in cross functional teams Experience in large scale, multi brand, or global enterprises; retail experience is advantageous Curious, delivery focused and keen to learn
Lead Data Scientist Permanent, Full-time Hybrid - remote with travel to our offices 1-2 times per month (Bristol, Manchester, London) Job Purpose This is an exciting opportunity to join Bupa Dental Care's Data Science team as a Lead Data Scientist, playing a key role in advancing AI and machine learning to improve patient outcomes, optimise practice performance, and enhance operational efficiency. You will work closely with teams across clinical, operations, product, and technology, contributing to BDC's ambition to use data and AI responsibly, ethically, and at scale. Our Vision for the D&A team is to unlock the full potential of our data - driving smarter decisions, empowering our people and creating lasting impact for our customers. In this role, you will lead the delivery of impactful, scalable AI solutions, manage and mentor data scientists, and help shape the technical direction of data science at BDC while ensuring alignment with business priorities and Responsible AI principles. Key Responsibilities Lead the design, development, and delivery of AI and machine learning solutions across patient journeys, clinical risk, practice performance, and operational efficiency Manage and mentor a team of data scientists, fostering a collaborative, high performing culture focused on quality, innovation, and continuous improvement Own end to end delivery of data science initiatives, including problem definition, business case development, feature engineering, model development, deployment, and monitoring Apply data science to real world healthcare challenges, including forecasting patient demand, optimising service capacity, predicting clinical risks and outcomes, and improving practice performance Collaborate closely with clinical, operational, and product stakeholders, acting as a key partner to business units and ensuring solutions deliver measurable impact Drive adoption of scalable, cloud based ML solutions, ensuring alignment with best practices in MLOps, model governance, and lifecycle management Skills & Experience Proven experience leading data science delivery, with a strong track record of deploying impactful AI/ML solutions in healthcare, dental, insurance, or regulated environments Strong hands on expertise in Python and SQL Experience working with cloud platforms such as Azure, GCP, or Snowflake Experience delivering end to end machine learning solutions, from exploration through to production deployment Strong understanding of machine learning workflows, MLOps, and scalable model deployment Experience managing or mentoring data scientists Desirable Experience working with clinical or dental data Experience in forecasting, optimisation, or predictive modelling in healthcare contexts Familiarity with Azure DevOps (Boards, Repos, Pipelines) or similar tools Experience working with unstructured data (e.g. clinical notes, imaging) Interest in ethical and responsible AI Benefits 25 days holiday, plus the option to buy more. Discounts in over 7,000 retailers, discounted gym membership and discounted dental insurance. Health Trust - our bespoke employee private healthcare plan, providing healthcare cover with no medical underwriting for colleagues and their families. Access to remote GP and nurse services, physiotherapy, and mental health support. MyHealthcare Allowance, an annual allowance which is redeemable against a menu of Bupa healthcare products. Early access to your earned wages through Wagestream. Cycle to work scheme. And many more, just ask Bupa takes pride in being a Level 2 Disability Confident Employer and will aim to offer an interview/assessment to disabled applicants who best meet the minimum criteria for the role. We are committed to ensuring you are treated fairly during the recruitment process and offer reasonable adjustments to anyone who may benefit from accommodations to the recruitment process. Bupa Dental Care is an equal opportunities employer.
08/06/2026
Full time
Lead Data Scientist Permanent, Full-time Hybrid - remote with travel to our offices 1-2 times per month (Bristol, Manchester, London) Job Purpose This is an exciting opportunity to join Bupa Dental Care's Data Science team as a Lead Data Scientist, playing a key role in advancing AI and machine learning to improve patient outcomes, optimise practice performance, and enhance operational efficiency. You will work closely with teams across clinical, operations, product, and technology, contributing to BDC's ambition to use data and AI responsibly, ethically, and at scale. Our Vision for the D&A team is to unlock the full potential of our data - driving smarter decisions, empowering our people and creating lasting impact for our customers. In this role, you will lead the delivery of impactful, scalable AI solutions, manage and mentor data scientists, and help shape the technical direction of data science at BDC while ensuring alignment with business priorities and Responsible AI principles. Key Responsibilities Lead the design, development, and delivery of AI and machine learning solutions across patient journeys, clinical risk, practice performance, and operational efficiency Manage and mentor a team of data scientists, fostering a collaborative, high performing culture focused on quality, innovation, and continuous improvement Own end to end delivery of data science initiatives, including problem definition, business case development, feature engineering, model development, deployment, and monitoring Apply data science to real world healthcare challenges, including forecasting patient demand, optimising service capacity, predicting clinical risks and outcomes, and improving practice performance Collaborate closely with clinical, operational, and product stakeholders, acting as a key partner to business units and ensuring solutions deliver measurable impact Drive adoption of scalable, cloud based ML solutions, ensuring alignment with best practices in MLOps, model governance, and lifecycle management Skills & Experience Proven experience leading data science delivery, with a strong track record of deploying impactful AI/ML solutions in healthcare, dental, insurance, or regulated environments Strong hands on expertise in Python and SQL Experience working with cloud platforms such as Azure, GCP, or Snowflake Experience delivering end to end machine learning solutions, from exploration through to production deployment Strong understanding of machine learning workflows, MLOps, and scalable model deployment Experience managing or mentoring data scientists Desirable Experience working with clinical or dental data Experience in forecasting, optimisation, or predictive modelling in healthcare contexts Familiarity with Azure DevOps (Boards, Repos, Pipelines) or similar tools Experience working with unstructured data (e.g. clinical notes, imaging) Interest in ethical and responsible AI Benefits 25 days holiday, plus the option to buy more. Discounts in over 7,000 retailers, discounted gym membership and discounted dental insurance. Health Trust - our bespoke employee private healthcare plan, providing healthcare cover with no medical underwriting for colleagues and their families. Access to remote GP and nurse services, physiotherapy, and mental health support. MyHealthcare Allowance, an annual allowance which is redeemable against a menu of Bupa healthcare products. Early access to your earned wages through Wagestream. Cycle to work scheme. And many more, just ask Bupa takes pride in being a Level 2 Disability Confident Employer and will aim to offer an interview/assessment to disabled applicants who best meet the minimum criteria for the role. We are committed to ensuring you are treated fairly during the recruitment process and offer reasonable adjustments to anyone who may benefit from accommodations to the recruitment process. Bupa Dental Care is an equal opportunities employer.
Location: Cheadle (hybrid working 3 office days per week) - regular travel to our London office will be required. Employment Type: Permanent, full time Additional Benefits: Annual Bonus, Cash-Car Allowance & Private Medical Insurance As a Lead Data Scientist within AA-X, you'll be part of the UK's largest and most trusted driving company, developing and testing human centric products and services fast; whilst giving AA members first access to everything we build. This is the job We are looking for a Lead Data Scientist to join our innovation focused data team, where you will play a pivotal role in shaping how advanced analytics, machine learning and AI drive both business performance and customer outcomes. In this highly visible role, you will lead the development of high impact data science solutions, transforming complex data into actionable insights that directly influence product strategy and operational direction. You will bring deep technical data science expertise alongside strong commercial awareness, enabling you to operate confidently at both a hands on and strategic level. Working closely with senior stakeholders, you will translate analytical outputs into clear strategic roadmaps, helping to prioritise opportunities and embed data science at the heart of decision making. We are looking for someone who challenges thinking, brings fresh ideas, and thrives in a fast paced, collaborative environment where data is central to shaping the future. What will I be doing? Develop and deploy advanced machine learning and statistical models to solve complex business challenges Translate technical outputs into clear strategic recommendations and data driven roadmaps Lead, mentor and develop a small team of data scientists, fostering a high performance culture Partner with senior stakeholders to shape priorities, influence decisions, and drive adoption of data led solutions Design and deliver scalable data products in collaboration with data engineering teams Identify and prioritise a pipeline of high value data science opportunities aligned to business goals What do I need? Strong technical expertise in data science, including machine learning, statistical modelling and optimisation techniques Advanced proficiency in tools such as Python, R, Spark and modern data platforms (e.g. Databricks) Proven ability to translate complex analytical outputs into business strategy and influence senior stakeholders Experience leading or mentoring data science teams and delivering through others Track record of delivering impactful, production ready data science solutions Excellent communication skills with the ability to engage both technical and non technical audiences Additional information We're always looking to recognise and reward our employees for the work they do. As a valued member of The AA team, you'll have access to a range of benefits including: 25 days annual leave plus bank holidays + holiday buying scheme Worksave pension scheme with up to 7% employer contribution Free AA breakdown membership from Day 1 plus 50% discount for family and friends Discounts on AA products including car and home insurance Employee discount scheme that gives you access to a car salary sacrifice scheme plus great discounts on healthcare, shopping, holidays and more Company funded life assurance Diverse learning and development opportunities to support you to progress in your career Dedicated Employee Assistance Programme and a 24/7 remote GP service for you and your family We're an equal opportunities employer and welcome applications from everyone. The AA values diversity and the difference this brings to our culture and our customers. We actively seek people from diverse backgrounds to join us and become part of an inclusive company where you can be yourself, be empowered to be your best and feel like you truly belong. We have five communities to bring together people with shared characteristics and backgrounds and drive positive change.
08/06/2026
Full time
Location: Cheadle (hybrid working 3 office days per week) - regular travel to our London office will be required. Employment Type: Permanent, full time Additional Benefits: Annual Bonus, Cash-Car Allowance & Private Medical Insurance As a Lead Data Scientist within AA-X, you'll be part of the UK's largest and most trusted driving company, developing and testing human centric products and services fast; whilst giving AA members first access to everything we build. This is the job We are looking for a Lead Data Scientist to join our innovation focused data team, where you will play a pivotal role in shaping how advanced analytics, machine learning and AI drive both business performance and customer outcomes. In this highly visible role, you will lead the development of high impact data science solutions, transforming complex data into actionable insights that directly influence product strategy and operational direction. You will bring deep technical data science expertise alongside strong commercial awareness, enabling you to operate confidently at both a hands on and strategic level. Working closely with senior stakeholders, you will translate analytical outputs into clear strategic roadmaps, helping to prioritise opportunities and embed data science at the heart of decision making. We are looking for someone who challenges thinking, brings fresh ideas, and thrives in a fast paced, collaborative environment where data is central to shaping the future. What will I be doing? Develop and deploy advanced machine learning and statistical models to solve complex business challenges Translate technical outputs into clear strategic recommendations and data driven roadmaps Lead, mentor and develop a small team of data scientists, fostering a high performance culture Partner with senior stakeholders to shape priorities, influence decisions, and drive adoption of data led solutions Design and deliver scalable data products in collaboration with data engineering teams Identify and prioritise a pipeline of high value data science opportunities aligned to business goals What do I need? Strong technical expertise in data science, including machine learning, statistical modelling and optimisation techniques Advanced proficiency in tools such as Python, R, Spark and modern data platforms (e.g. Databricks) Proven ability to translate complex analytical outputs into business strategy and influence senior stakeholders Experience leading or mentoring data science teams and delivering through others Track record of delivering impactful, production ready data science solutions Excellent communication skills with the ability to engage both technical and non technical audiences Additional information We're always looking to recognise and reward our employees for the work they do. As a valued member of The AA team, you'll have access to a range of benefits including: 25 days annual leave plus bank holidays + holiday buying scheme Worksave pension scheme with up to 7% employer contribution Free AA breakdown membership from Day 1 plus 50% discount for family and friends Discounts on AA products including car and home insurance Employee discount scheme that gives you access to a car salary sacrifice scheme plus great discounts on healthcare, shopping, holidays and more Company funded life assurance Diverse learning and development opportunities to support you to progress in your career Dedicated Employee Assistance Programme and a 24/7 remote GP service for you and your family We're an equal opportunities employer and welcome applications from everyone. The AA values diversity and the difference this brings to our culture and our customers. We actively seek people from diverse backgrounds to join us and become part of an inclusive company where you can be yourself, be empowered to be your best and feel like you truly belong. We have five communities to bring together people with shared characteristics and backgrounds and drive positive change.
JD Sports- Head Office, Warwick House, Bury, Bury, United Kingdom Job Description Established in 1981 with a single store in the Northwest of England, the JD Group is a leading omni-channel retailer of Sports Fashion, Outdoors and Gyms with our colleagues working in stores across several retail fascias in many markets around the world. JD Sports Fashion Plc was listed on the London Stock Exchange in 1996 and has been a FTSE100 publicly quoted company since 2019 and continues to grow in the UK and internationally. We want to be the leading global omnichannel retailer in the sports and outdoor industry. To be a part of this successful company and help us to achieve this you will have the desire to ingrain our strategic goals of being a people-led, innovative and customer focused organisation which provides operational excellence whilst identifying new areas of growth as part of our day to day objectives. Role Overview: The Senior AI Engineer is a senior individual contributor responsible for architecting, building and scaling production grade AI platforms and generative AI systems across JD Group. Reporting into the Head of Data Science & AI, the role focuses on the engineering, operationalisation and governance of large scale AI solutions, including LLM based applications, agentic workflows and retrieval augmented generation systems. Working closely with Senior Data Scientists, Data Engineering, Platform and Product teams, the Senior AI Engineer ensures AI solutions are reliable, secure, cost effective and embedded into core business processes. This role carries significant technical leadership, mentorship and influence across the wider Data & AI community. Responsibilities: AI Platform & Solution Engineering Architect, develop and deploy enterprise scale AI and GenAI solutions including LLM applications, agentic workflows and tool using agents Design, implement and optimise production grade RAG architectures with strong performance, scalability and latency characteristics Build AI services, microservices, inference pipelines and platform components using modern engineering frameworks and patterns Own technical decisions across AI system design, orchestration, routing, caching and runtime optimisation Production Readiness, LLMOps & MLOps Define and implement standards for LLMOps, MLOps, monitoring, observability, safety and compliance Ensure AI systems are robust, monitored, explainable and suitable for long term production use Partner closely with Platform, DevOps and Security teams to deliver cloud native, secure and scalable solutions on GCP Drive cost efficient AI deployment strategies including prompt optimisation, model selection, caching, distillation and compute optimisation Embed responsible AI principles into system design, including safety, security, bias mitigation and data protection Support governance frameworks for model usage, evaluation, auditability and risk management Develop automated evaluation, testing and quality assurance frameworks for LLM based systems Stakeholder Partnership & Influence Work closely with Senior Data Scientists to productionise AI driven analytical and decisioning solutions Partner with Product, Engineering and Architecture leaders to shape AI solution design and delivery Contribute to strategic decisions on AI infrastructure, architecture and long term platform roadmap Evaluate and onboard AI vendors and third party platforms, prioritising buy first solutions where appropriate Capability Building & Mentorship Provide technical mentorship and guidance to AI Engineers and adjacent engineering teams Contribute to shared platforms, reusable components, reference architectures and best practices Stay current with advances in generative AI, agentic systems and AI infrastructure, identifying pragmatic opportunities to apply new capabilities Role Objectives & KPIs Deliver production grade AI platforms and systems that generate measurable business value Ensure AI solutions are scalable, reliable, secure and cost effective Reduce operational risk through strong governance, automation and engineering standards Successful end to end delivery of complex AI initiatives to agreed quality and timelines Strengthen trust in AI as a decision making and operational capability Strong stakeholder satisfaction and trust in AI delivery Act as a senior technical role model within the Data Science & AI function Skills and Experience: Significant experience in AI Engineering, ML Engineering or Software Engineering with proven production delivery Deep expertise in LLMs, generative AI, agentic systems, RAG architectures and vector databases Strong experience building distributed systems, microservices and scalable API driven platforms Advanced experience with GCP AI stack (Vertex AI, BigQuery, Cloud Run, Cloud Functions, Cloud SQL, Agent Engine, AlloyDB etc.) Strong Python skills and experience building production grade AI services Experience implementing LLMOps, MLOps, CI/CD and infrastructure automation Expertise in developing applications with React, NextJS. Strong understanding of responsible AI, security, governance and data compliance Ability to influence technical direction and communicate effectively with senior stakeholders Experience in large scale, multi brand, or global enterprises; retail experience is advantageous Delivery focused, pragmatic, and accountable Line management/mentoring experience will be preferable We know our colleagues work tirelessly to make JD Sports the success it is today and in turn, we offer them some amazing benefits including staff Discount On JD Group and other brands within the organisation and personal development opportunities to learn and develop at work.
08/06/2026
Full time
JD Sports- Head Office, Warwick House, Bury, Bury, United Kingdom Job Description Established in 1981 with a single store in the Northwest of England, the JD Group is a leading omni-channel retailer of Sports Fashion, Outdoors and Gyms with our colleagues working in stores across several retail fascias in many markets around the world. JD Sports Fashion Plc was listed on the London Stock Exchange in 1996 and has been a FTSE100 publicly quoted company since 2019 and continues to grow in the UK and internationally. We want to be the leading global omnichannel retailer in the sports and outdoor industry. To be a part of this successful company and help us to achieve this you will have the desire to ingrain our strategic goals of being a people-led, innovative and customer focused organisation which provides operational excellence whilst identifying new areas of growth as part of our day to day objectives. Role Overview: The Senior AI Engineer is a senior individual contributor responsible for architecting, building and scaling production grade AI platforms and generative AI systems across JD Group. Reporting into the Head of Data Science & AI, the role focuses on the engineering, operationalisation and governance of large scale AI solutions, including LLM based applications, agentic workflows and retrieval augmented generation systems. Working closely with Senior Data Scientists, Data Engineering, Platform and Product teams, the Senior AI Engineer ensures AI solutions are reliable, secure, cost effective and embedded into core business processes. This role carries significant technical leadership, mentorship and influence across the wider Data & AI community. Responsibilities: AI Platform & Solution Engineering Architect, develop and deploy enterprise scale AI and GenAI solutions including LLM applications, agentic workflows and tool using agents Design, implement and optimise production grade RAG architectures with strong performance, scalability and latency characteristics Build AI services, microservices, inference pipelines and platform components using modern engineering frameworks and patterns Own technical decisions across AI system design, orchestration, routing, caching and runtime optimisation Production Readiness, LLMOps & MLOps Define and implement standards for LLMOps, MLOps, monitoring, observability, safety and compliance Ensure AI systems are robust, monitored, explainable and suitable for long term production use Partner closely with Platform, DevOps and Security teams to deliver cloud native, secure and scalable solutions on GCP Drive cost efficient AI deployment strategies including prompt optimisation, model selection, caching, distillation and compute optimisation Embed responsible AI principles into system design, including safety, security, bias mitigation and data protection Support governance frameworks for model usage, evaluation, auditability and risk management Develop automated evaluation, testing and quality assurance frameworks for LLM based systems Stakeholder Partnership & Influence Work closely with Senior Data Scientists to productionise AI driven analytical and decisioning solutions Partner with Product, Engineering and Architecture leaders to shape AI solution design and delivery Contribute to strategic decisions on AI infrastructure, architecture and long term platform roadmap Evaluate and onboard AI vendors and third party platforms, prioritising buy first solutions where appropriate Capability Building & Mentorship Provide technical mentorship and guidance to AI Engineers and adjacent engineering teams Contribute to shared platforms, reusable components, reference architectures and best practices Stay current with advances in generative AI, agentic systems and AI infrastructure, identifying pragmatic opportunities to apply new capabilities Role Objectives & KPIs Deliver production grade AI platforms and systems that generate measurable business value Ensure AI solutions are scalable, reliable, secure and cost effective Reduce operational risk through strong governance, automation and engineering standards Successful end to end delivery of complex AI initiatives to agreed quality and timelines Strengthen trust in AI as a decision making and operational capability Strong stakeholder satisfaction and trust in AI delivery Act as a senior technical role model within the Data Science & AI function Skills and Experience: Significant experience in AI Engineering, ML Engineering or Software Engineering with proven production delivery Deep expertise in LLMs, generative AI, agentic systems, RAG architectures and vector databases Strong experience building distributed systems, microservices and scalable API driven platforms Advanced experience with GCP AI stack (Vertex AI, BigQuery, Cloud Run, Cloud Functions, Cloud SQL, Agent Engine, AlloyDB etc.) Strong Python skills and experience building production grade AI services Experience implementing LLMOps, MLOps, CI/CD and infrastructure automation Expertise in developing applications with React, NextJS. Strong understanding of responsible AI, security, governance and data compliance Ability to influence technical direction and communicate effectively with senior stakeholders Experience in large scale, multi brand, or global enterprises; retail experience is advantageous Delivery focused, pragmatic, and accountable Line management/mentoring experience will be preferable We know our colleagues work tirelessly to make JD Sports the success it is today and in turn, we offer them some amazing benefits including staff Discount On JD Group and other brands within the organisation and personal development opportunities to learn and develop at work.
Senior Security Engineer (AI & DevSecOps) at iProov About iProov iProov provides science-based biometric solutions that enable the world's most security-conscious organizations to streamline secure remote onboarding and authentication for digital and physical access. Our award-winning liveness technology and iSOC offer unmatched resilience against deepfakes and generative AI threats while ensuring effortless, scalable user experiences. Trusted by leading governments and enterprises, including the U.S. Department of Homeland Security, U.K. Home Office, GovTech Singapore, ING, and UBS, iProov sets the standard in biometric identity assurance. This global trust is built not only on our technology but on the strength of the people behind it. For us, diversity at iProov is about reflecting the customers we serve, holding the principles of equality and inclusion at the heart of everything we do and all that we stand for, embracing differences, creating possibilities, and growing together. We aim to foster a culture where individuals of all backgrounds feel confident in bringing their whole selves to work, feel included, and their talents are nurtured, empowering them to contribute fully to our purpose. The Role Reports to: Head of Cybersecurity Location: WeWork Waterloo - Hybrid Comp: $ (Base) + Company Performance Bonus (20%) + Share Options + US iProov Benefits The role was created specifically to provide the technical security depth that will allow us to accelerate our adoption of agentic AI, equipping developers and data scientists building our biometric products with the tools and workflows to use AI safely and at pace. You will work as the direct counterpart to our GRC focused InfoSec Manager, owning the engineering and implementation side of our security posture across cloud infrastructure, developer workflows, AI systems, and our core security toolstack. This is a role for someone who has built and shipped software or infrastructure and brings that experience into a security context. How you can make an impact Architect and deploy the secure technical framework that governs the security controls for how our developers and scientists use agentic AI, including AI coding assistants, autonomous agents, and LLM integrated tooling. Given that these systems can autonomously access data, execute code, and interact with external services, the guardrails you design will need to address a substantially broader attack surface than traditional AI tooling, and must hold up in a context where the underlying data is among the most sensitive we handle. Be the primary technical security voice in decisions around the use and deployment of externally developed AI, ensuring the right controls are in place from the onset. Continuously mature automated security controls into CI/CD pipelines and infrastructure as code deployments, championing the DevSecOps culture across a large engineering organisation. Take hands on ownership of our core security technology stack, including Wiz, CrowdStrike, Google SecOps, and Tailscale, ensuring these platforms are correctly configured, tuned, and integrated. Drive continuous technical delivery of strategic security initiatives, systematically identifying, triaging, and closing gaps across our cloud environments, internal networks, and developer workflows. Provide technical oversight of the security of the data pipelines feeding our internal AI systems and, critically, the permissions and access boundaries of agentic AI systems reaching out into other environments, enforcing the principle of least privilege, maintaining audit trails, and ensuring sensitive data and code integrity is handled with the rigour required. Complement the work of our existing biometric and product focused Red Team by owning security coverage of the DevSecOps surface, the build pipeline, internal toolchain, cloud environments and developer infrastructure. Act as the primary technical security partner to our GRC focused InfoSec Manager, translating governance and compliance mandates into concrete, automated engineering controls. Represent the technical security function in external audits. This includes presenting evidence of controls, articulating the security posture of our cloud and AI environments to auditors, and working closely with the InfoSec Manager to ensure the technical substance behind our compliance position is clearly and credibly communicated. Qualifications A foundational background in software engineering or DevOps before moving into a dedicated security role: you understand how code is written, tested, and deployed, and that experience is central to how you approach security problems. Proven, hands on experience securing modern cloud infrastructure and containerised environments, with a solid understanding of infrastructure as code principles and the security implications of how infrastructure is defined and provisioned. Proficiency in deploying and administering enterprise security platforms, ideally with direct experience managing tools spanning CNAPP, EDR, SIEM, and zero trust networking. A heavy and active user of AI in both professional and personal contexts, including agentic AI tools and coding assistants, with a grounded understanding of the evolving AI threat landscape, including model supply chain risks, prompt injection, data exfiltration, agent misuse, and LLM specific attack vectors. Scripting and automation capability, particularly in Python, to build internal tooling, automate security checks, and reduce reliance on manual processes across the security function. Prior experience or a demonstrated practical interest in securing AI workloads, data pipelines, and machine learning environments. The communication skills to collaborate effectively with highly technical stakeholders, champion security initiatives without hindering developer productivity, and translate risk into language that resonates with both engineering peers and business leadership, including the confidence to present technical security evidence clearly in formal external audit settings. Benefits 25 days Annual Leave, plus 8 Bank Holidays (more holiday with service - up to an extra 5 days off per year based on your continuous service) Growth Shares allocated after passing probation (6 months of service) Salary sacrifice schemes including: Pension, Cycle To Work and Electric Car Scheme Nursery Sacrifice Scheme Work Overseas Perk - Work globally for up to 2 weeks Life Assurance SmartHealth - Access to private GP, Psychologist, Nutritionist along with tailored fitness plans for both you and your family Benefit from personalized 1:1 career coaching with our in house Occupational Psychologist Award winning L&D platform with personal allocated training budgets Enhanced paid family leave Flexible hybrid working environment Free Barista Coffee/Tea, biscuits with fruit in the WeWork office Free access to WeWork discounts and free online well being sessions Vitality Health - a range of options available on this below The Vitality Programme includes a number of reward benefits that all employees have access to as part of the plan, for example: Private Health cover including Dental, Optical, and Audiology 50% off monthly gym memberships Apple watches significantly discounted based member vitality status Half price trainers with Runners Need Weekly rewards - Free coffee with Café Nero Monthly rewards - Free Cinema ticket Discounts on travel with Expedia (hotels) and Mr & Mrs Smith with discounts getting greater throughout the year based on a members vitality status Amazon prime free months based on activity Up to 25% cashback at Waitrose when buying healthy foods75% off stays at Champneys Health Spas Allen Carr's £299 no smoking programme for free Access to Vitality Healthy Mind with 30% off Headspace subscriptions and the ability to earn Vitality points for using Buddhify, Calm and Headspace Discounts on Weight Watchers As an equal opportunities employer, we encourage applications from people of all backgrounds. We're committed to building a workforce that is representative of the people we serve.
08/06/2026
Full time
Senior Security Engineer (AI & DevSecOps) at iProov About iProov iProov provides science-based biometric solutions that enable the world's most security-conscious organizations to streamline secure remote onboarding and authentication for digital and physical access. Our award-winning liveness technology and iSOC offer unmatched resilience against deepfakes and generative AI threats while ensuring effortless, scalable user experiences. Trusted by leading governments and enterprises, including the U.S. Department of Homeland Security, U.K. Home Office, GovTech Singapore, ING, and UBS, iProov sets the standard in biometric identity assurance. This global trust is built not only on our technology but on the strength of the people behind it. For us, diversity at iProov is about reflecting the customers we serve, holding the principles of equality and inclusion at the heart of everything we do and all that we stand for, embracing differences, creating possibilities, and growing together. We aim to foster a culture where individuals of all backgrounds feel confident in bringing their whole selves to work, feel included, and their talents are nurtured, empowering them to contribute fully to our purpose. The Role Reports to: Head of Cybersecurity Location: WeWork Waterloo - Hybrid Comp: $ (Base) + Company Performance Bonus (20%) + Share Options + US iProov Benefits The role was created specifically to provide the technical security depth that will allow us to accelerate our adoption of agentic AI, equipping developers and data scientists building our biometric products with the tools and workflows to use AI safely and at pace. You will work as the direct counterpart to our GRC focused InfoSec Manager, owning the engineering and implementation side of our security posture across cloud infrastructure, developer workflows, AI systems, and our core security toolstack. This is a role for someone who has built and shipped software or infrastructure and brings that experience into a security context. How you can make an impact Architect and deploy the secure technical framework that governs the security controls for how our developers and scientists use agentic AI, including AI coding assistants, autonomous agents, and LLM integrated tooling. Given that these systems can autonomously access data, execute code, and interact with external services, the guardrails you design will need to address a substantially broader attack surface than traditional AI tooling, and must hold up in a context where the underlying data is among the most sensitive we handle. Be the primary technical security voice in decisions around the use and deployment of externally developed AI, ensuring the right controls are in place from the onset. Continuously mature automated security controls into CI/CD pipelines and infrastructure as code deployments, championing the DevSecOps culture across a large engineering organisation. Take hands on ownership of our core security technology stack, including Wiz, CrowdStrike, Google SecOps, and Tailscale, ensuring these platforms are correctly configured, tuned, and integrated. Drive continuous technical delivery of strategic security initiatives, systematically identifying, triaging, and closing gaps across our cloud environments, internal networks, and developer workflows. Provide technical oversight of the security of the data pipelines feeding our internal AI systems and, critically, the permissions and access boundaries of agentic AI systems reaching out into other environments, enforcing the principle of least privilege, maintaining audit trails, and ensuring sensitive data and code integrity is handled with the rigour required. Complement the work of our existing biometric and product focused Red Team by owning security coverage of the DevSecOps surface, the build pipeline, internal toolchain, cloud environments and developer infrastructure. Act as the primary technical security partner to our GRC focused InfoSec Manager, translating governance and compliance mandates into concrete, automated engineering controls. Represent the technical security function in external audits. This includes presenting evidence of controls, articulating the security posture of our cloud and AI environments to auditors, and working closely with the InfoSec Manager to ensure the technical substance behind our compliance position is clearly and credibly communicated. Qualifications A foundational background in software engineering or DevOps before moving into a dedicated security role: you understand how code is written, tested, and deployed, and that experience is central to how you approach security problems. Proven, hands on experience securing modern cloud infrastructure and containerised environments, with a solid understanding of infrastructure as code principles and the security implications of how infrastructure is defined and provisioned. Proficiency in deploying and administering enterprise security platforms, ideally with direct experience managing tools spanning CNAPP, EDR, SIEM, and zero trust networking. A heavy and active user of AI in both professional and personal contexts, including agentic AI tools and coding assistants, with a grounded understanding of the evolving AI threat landscape, including model supply chain risks, prompt injection, data exfiltration, agent misuse, and LLM specific attack vectors. Scripting and automation capability, particularly in Python, to build internal tooling, automate security checks, and reduce reliance on manual processes across the security function. Prior experience or a demonstrated practical interest in securing AI workloads, data pipelines, and machine learning environments. The communication skills to collaborate effectively with highly technical stakeholders, champion security initiatives without hindering developer productivity, and translate risk into language that resonates with both engineering peers and business leadership, including the confidence to present technical security evidence clearly in formal external audit settings. Benefits 25 days Annual Leave, plus 8 Bank Holidays (more holiday with service - up to an extra 5 days off per year based on your continuous service) Growth Shares allocated after passing probation (6 months of service) Salary sacrifice schemes including: Pension, Cycle To Work and Electric Car Scheme Nursery Sacrifice Scheme Work Overseas Perk - Work globally for up to 2 weeks Life Assurance SmartHealth - Access to private GP, Psychologist, Nutritionist along with tailored fitness plans for both you and your family Benefit from personalized 1:1 career coaching with our in house Occupational Psychologist Award winning L&D platform with personal allocated training budgets Enhanced paid family leave Flexible hybrid working environment Free Barista Coffee/Tea, biscuits with fruit in the WeWork office Free access to WeWork discounts and free online well being sessions Vitality Health - a range of options available on this below The Vitality Programme includes a number of reward benefits that all employees have access to as part of the plan, for example: Private Health cover including Dental, Optical, and Audiology 50% off monthly gym memberships Apple watches significantly discounted based member vitality status Half price trainers with Runners Need Weekly rewards - Free coffee with Café Nero Monthly rewards - Free Cinema ticket Discounts on travel with Expedia (hotels) and Mr & Mrs Smith with discounts getting greater throughout the year based on a members vitality status Amazon prime free months based on activity Up to 25% cashback at Waitrose when buying healthy foods75% off stays at Champneys Health Spas Allen Carr's £299 no smoking programme for free Access to Vitality Healthy Mind with 30% off Headspace subscriptions and the ability to earn Vitality points for using Buddhify, Calm and Headspace Discounts on Weight Watchers As an equal opportunities employer, we encourage applications from people of all backgrounds. We're committed to building a workforce that is representative of the people we serve.
Lead Data Scientist - OpenExpert.ai Department: Studio Employment Type: Full Time Location: Cambridge Description This is an early stage, hands on builder role with a path to Head / Chief Data Scientist as the company scales. We are only considering candidates who: Have worked in startups or early stage environments Are comfortable building from scratch (0 1) Want to grow into a leadership role over time, not step into a large pre built team If you are primarily looking for a senior executive role with an established team and structure, this role is likely not the right fit. About OpenExpert.AI OpenExpert.AI is building the intelligence layer for power operations - an AI platform designed to help operations and maintenance teams diagnose issues faster, preserve institutional knowledge, reduce downtime, and improve decision making in high stakes industrial environments. OpenExpert.AI is a venture built within C10 Labs, focused on creating category defining AI first companies. The Role: Lead Data Scientist (Founding Team) We're looking for a senior, hands on data scientist to build the core intelligence layer of the platform. This is not a pure management role. You will be responsible for designing, building, and deploying real AI systems, working directly with product, engineering, and customers. Over time, you will have the opportunity to build and lead the data science function as the company grows. What You'll Do Build the Core AI System (0 1) Design and develop AI/ML systems for diagnostics, anomaly detection, and decision support Work with time series, sensor data, text, and operational data in real world environments Build and deploy models into production, not just prototypes Turn Data into Intelligence Transform telemetry, manuals, work orders, and engineering documents into actionable insights Develop systems for root cause analysis, predictive maintenance, and knowledge capture Contribute to multimodal AI systems that combine structured and unstructured data Work Across Product & Engineering Partner closely with product and engineering to ship quickly and iterate Help define what to build, not just how to build it Support early pilots tied to real customer outcomes (diagnostics, uptime, efficiency) Lay the Foundation for Scale Establish best practices for model development, evaluation, and deployment Contribute to explainability, reliability, and system performance Help shape the future data science function and roadmap Who You Are Builder Mindset (Required) Experience working in a startup or early stage environment Have built and shipped ML/AI systems from scratch Comfortable being hands on and scrappyStrong bias for execution, speed, and ownership Technical Depth Strong experience in machine learning, data science, or applied AI Experience with time series data, anomaly detection, or predictive systems Familiarity with LLMs, retrieval systems, or multimodal data is a plus Solid engineering skills (Python, production systems, APIs, cloud environments) Real World Systems Experience Experience deploying models into production environments Comfortable working with messy, real world data Ability to balance model performance with practical constraints Growth Potential Interested in growing into a leadership role (Head / Chief Data Scientist) Able to mentor others and help build a team over time Interested in shaping both technical direction and team development Bonus (Not Required) Experience in energy, industrial systems, or manufacturing Familiarity with SCADA/OT systems, IoT, or operational data environments Background in predictive maintenance or decision support systems What This Role Is NOT Are looking for a pure leadership role without hands on work Prefer working with large, structured teams and clean data Have not worked in early stage or ambiguous environments What You'll Get Early team member with high ownership and impact Clear path to Head / Chief Data Scientist as the company grows Equity in a venture backed company Backing from C10 Labs (capital, talent, and support) Opportunity to build AI systems in real world, high stakes environments Compensation Equity + salary (post fundraise structure) Why This Role The energy sector is facing a massive knowledge and workforce gap. OpenExpert.AI is building the system to capture expertise and make it usable in real time. This is an opportunity to: Build from 0 1 Work on high impact, real world problemsHelp define a category at the intersection of AI, energy, and industrial systems
08/06/2026
Full time
Lead Data Scientist - OpenExpert.ai Department: Studio Employment Type: Full Time Location: Cambridge Description This is an early stage, hands on builder role with a path to Head / Chief Data Scientist as the company scales. We are only considering candidates who: Have worked in startups or early stage environments Are comfortable building from scratch (0 1) Want to grow into a leadership role over time, not step into a large pre built team If you are primarily looking for a senior executive role with an established team and structure, this role is likely not the right fit. About OpenExpert.AI OpenExpert.AI is building the intelligence layer for power operations - an AI platform designed to help operations and maintenance teams diagnose issues faster, preserve institutional knowledge, reduce downtime, and improve decision making in high stakes industrial environments. OpenExpert.AI is a venture built within C10 Labs, focused on creating category defining AI first companies. The Role: Lead Data Scientist (Founding Team) We're looking for a senior, hands on data scientist to build the core intelligence layer of the platform. This is not a pure management role. You will be responsible for designing, building, and deploying real AI systems, working directly with product, engineering, and customers. Over time, you will have the opportunity to build and lead the data science function as the company grows. What You'll Do Build the Core AI System (0 1) Design and develop AI/ML systems for diagnostics, anomaly detection, and decision support Work with time series, sensor data, text, and operational data in real world environments Build and deploy models into production, not just prototypes Turn Data into Intelligence Transform telemetry, manuals, work orders, and engineering documents into actionable insights Develop systems for root cause analysis, predictive maintenance, and knowledge capture Contribute to multimodal AI systems that combine structured and unstructured data Work Across Product & Engineering Partner closely with product and engineering to ship quickly and iterate Help define what to build, not just how to build it Support early pilots tied to real customer outcomes (diagnostics, uptime, efficiency) Lay the Foundation for Scale Establish best practices for model development, evaluation, and deployment Contribute to explainability, reliability, and system performance Help shape the future data science function and roadmap Who You Are Builder Mindset (Required) Experience working in a startup or early stage environment Have built and shipped ML/AI systems from scratch Comfortable being hands on and scrappyStrong bias for execution, speed, and ownership Technical Depth Strong experience in machine learning, data science, or applied AI Experience with time series data, anomaly detection, or predictive systems Familiarity with LLMs, retrieval systems, or multimodal data is a plus Solid engineering skills (Python, production systems, APIs, cloud environments) Real World Systems Experience Experience deploying models into production environments Comfortable working with messy, real world data Ability to balance model performance with practical constraints Growth Potential Interested in growing into a leadership role (Head / Chief Data Scientist) Able to mentor others and help build a team over time Interested in shaping both technical direction and team development Bonus (Not Required) Experience in energy, industrial systems, or manufacturing Familiarity with SCADA/OT systems, IoT, or operational data environments Background in predictive maintenance or decision support systems What This Role Is NOT Are looking for a pure leadership role without hands on work Prefer working with large, structured teams and clean data Have not worked in early stage or ambiguous environments What You'll Get Early team member with high ownership and impact Clear path to Head / Chief Data Scientist as the company grows Equity in a venture backed company Backing from C10 Labs (capital, talent, and support) Opportunity to build AI systems in real world, high stakes environments Compensation Equity + salary (post fundraise structure) Why This Role The energy sector is facing a massive knowledge and workforce gap. OpenExpert.AI is building the system to capture expertise and make it usable in real time. This is an opportunity to: Build from 0 1 Work on high impact, real world problemsHelp define a category at the intersection of AI, energy, and industrial systems
Overview CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . We're proud to be a Living Wage accredited Employer. What You'll Do The Monolith Data Science team is building a layered reliability platform that shifts CoreWeave from reactive troubleshooting to proactive reliability engineering. The platform spans telemetry ingestion, feature engineering, anomaly detection, failure prediction, distributed straggler detection, and agentic root cause analysis. We partner closely with Fleet, Infrastructure, and AI Platform teams to improve cluster reliability, increase effective utilization (MFU), reduce MTTR, and protect uptime and revenue. About the role As a Data Science Researcher, you will develop advanced statistical models and machine learning methodologies to optimize GPU utilization, workload scheduling, and infrastructure efficiency. You will design experiments, analyze large-scale system telemetry data, and prototype predictive and optimization algorithms that directly inform production systems. This role blends research rigor with real-world impact, turning complex infrastructure data into measurable improvements in performance and cost. You will collaborate cross-functionally to translate research insights into deployable solutions. Who You Are MS or PhD in Computer Science, Statistics, Applied Mathematics, Machine Learning, or related quantitative field 8+ years (or equivalent research experience) applying statistical modeling or machine learning to large-scale datasets Strong proficiency in Python and scientific computing libraries (NumPy, pandas, SciPy, scikit-learn, PyTorch or TensorFlow) Demonstrated experience designing and analyzing controlled experiments (A/B testing, causal inference, hypothesis testing) Experience working with distributed data systems (Spark, Ray, Dask, or similar) Proficiency in SQL and working with large-scale structured datasets Experience building and validating predictive models in production or research environments Strong understanding of optimization techniques (linear programming, convex optimization, stochastic optimization, or reinforcement learning) Experience working with time-series data and performance telemetry Ability to translate research findings into production-ready prototypes Preferred PhD with published research in systems optimization, distributed computing, ML systems, or performance modeling Experience with GPU workloads, distributed training, or AI infrastructure Familiarity with Kubernetes, containerized workloads, or cloud-native systems Experience developing reinforcement learning or adaptive scheduling systems Background in capacity planning, forecasting, or resource allocation modeling Contributions to open-source ML or systems projects Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams - even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. You love uncovering hidden failure patterns in massive, noisy infrastructure datasets You're curious about building autonomous, agentic systems that investigate and explain system behavior You're an expert in reinforcement learning, predictive modeling, or large-scale data analysis Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: Be Curious at Your Core Act Like an Owner Empower Employees Deliver Best-in-Class Client Experiences Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! Compliance and Privacy To fulfil our obligation to protect client data, successful applicants offered employment with CoreWeave will be required to complete a basic criminal record check, conducted in compliance with GDPR. Employment offers are conditional upon receiving satisfactory check results. What We Offer In addition to a competitive salary, we offer a variety of benefits to support your needs, including: Family-level Medical Insurance Family-level Dental Insurance Generous Pension Contribution Life Assurance at 4x Salary Critical Illness Cover Employee Assistance Programme Tuition Reimbursement Work culture focused on innovative disruption Benefits may vary by location. Our Workplace While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration. CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. Export Control Compliance: This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be a U.S. person or eligible to access without a required export authorization.
08/06/2026
Full time
Overview CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . We're proud to be a Living Wage accredited Employer. What You'll Do The Monolith Data Science team is building a layered reliability platform that shifts CoreWeave from reactive troubleshooting to proactive reliability engineering. The platform spans telemetry ingestion, feature engineering, anomaly detection, failure prediction, distributed straggler detection, and agentic root cause analysis. We partner closely with Fleet, Infrastructure, and AI Platform teams to improve cluster reliability, increase effective utilization (MFU), reduce MTTR, and protect uptime and revenue. About the role As a Data Science Researcher, you will develop advanced statistical models and machine learning methodologies to optimize GPU utilization, workload scheduling, and infrastructure efficiency. You will design experiments, analyze large-scale system telemetry data, and prototype predictive and optimization algorithms that directly inform production systems. This role blends research rigor with real-world impact, turning complex infrastructure data into measurable improvements in performance and cost. You will collaborate cross-functionally to translate research insights into deployable solutions. Who You Are MS or PhD in Computer Science, Statistics, Applied Mathematics, Machine Learning, or related quantitative field 8+ years (or equivalent research experience) applying statistical modeling or machine learning to large-scale datasets Strong proficiency in Python and scientific computing libraries (NumPy, pandas, SciPy, scikit-learn, PyTorch or TensorFlow) Demonstrated experience designing and analyzing controlled experiments (A/B testing, causal inference, hypothesis testing) Experience working with distributed data systems (Spark, Ray, Dask, or similar) Proficiency in SQL and working with large-scale structured datasets Experience building and validating predictive models in production or research environments Strong understanding of optimization techniques (linear programming, convex optimization, stochastic optimization, or reinforcement learning) Experience working with time-series data and performance telemetry Ability to translate research findings into production-ready prototypes Preferred PhD with published research in systems optimization, distributed computing, ML systems, or performance modeling Experience with GPU workloads, distributed training, or AI infrastructure Familiarity with Kubernetes, containerized workloads, or cloud-native systems Experience developing reinforcement learning or adaptive scheduling systems Background in capacity planning, forecasting, or resource allocation modeling Contributions to open-source ML or systems projects Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams - even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. You love uncovering hidden failure patterns in massive, noisy infrastructure datasets You're curious about building autonomous, agentic systems that investigate and explain system behavior You're an expert in reinforcement learning, predictive modeling, or large-scale data analysis Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: Be Curious at Your Core Act Like an Owner Empower Employees Deliver Best-in-Class Client Experiences Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! Compliance and Privacy To fulfil our obligation to protect client data, successful applicants offered employment with CoreWeave will be required to complete a basic criminal record check, conducted in compliance with GDPR. Employment offers are conditional upon receiving satisfactory check results. What We Offer In addition to a competitive salary, we offer a variety of benefits to support your needs, including: Family-level Medical Insurance Family-level Dental Insurance Generous Pension Contribution Life Assurance at 4x Salary Critical Illness Cover Employee Assistance Programme Tuition Reimbursement Work culture focused on innovative disruption Benefits may vary by location. Our Workplace While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration. CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. Export Control Compliance: This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be a U.S. person or eligible to access without a required export authorization.
IDBS empowers BioPharma organizations to unlock the full potential of AI/ML to improve the lives and patient outcomes. As a trusted long-standing partner to 80% of the top 20 global BioPharma companies1, we deliver cloud-native software and services built specifically for the rapidly evolving needs of the industry. A Danaher company over 35 years of scientific informatics expertise, IDBS helps organizations design, execute and orchestrate processes; manage, contextualize and structure data; and gain valuable insights throughout the product lifecycle, from R&D through manufacturing. Widely recognised for our E-WorkBook platform, we've expanded our portfolio with flexible and scalable IDBSPolar and PIMS cloud platforms, enabling scientists to make smarter, faster decisions with confidence in both GxP and non-GxP environments. Do you want to work in a dynamic, fast paced, high performing, safe to fail and fun environment which is founded on trust, empowerment and autonomy? Do you enjoy solving complex customer problems as a team? What we'll get you doing: Lead cross-functional initiatives, supported by Engineering Director, to enhance quality, security, reliability and productivity. This includes championing best practices, strengthening data platform, integrating AI-driven tooling, and applying Agile ways of working to accelerate delivery. Champion a strong customer-focused culture by ensuring engineering decisions align with user needs, improve customer experience and deliver measurable value. Drive continuous improvement and innovation by optimising processes, reducing friction and raising engineering standards across the organization. Develop and coach your team to deliver high-quality software through guidance on modern engineering practices, architectural patterns and clean coding principles. Experience with Python, Java and frontend technologies like React is a plus. Grow and develop engineering talent through structured performance reviews, regular 1-2-1s, and clear personal development objectives. 21s, Strengthen collaboration and communication by working closely with Scrum Masters, Strategy, Product, Architecture, Quality and other key stakeholders. Instil a start-up mindset by promoting speed, ownership and experimentation to drive innovation and impactful delivery. What success looks like: Proven leadership in building highly engaged engineering teams that consistently deliver high quality software through strong management and Agile delivery practices. Effective people management grounded in active listening, supporting individual growth, and fostering diversity in a psychologically safe environment. Clear communication of technical concepts to both technical and nontechnical audiences. Consistent delivery of secure and high-quality engineering outcomes. Continuous improvement to drive delivery efficiency incrementally. Effective collaboration across cross functional teams to achieve aligned customer-focused results. A proactive, innovative mindset that embraces ownership, experimentation and modern engineering practices. Nice to have: Familiarity with AI driven engineering tools and data-centric development practices. Background in AWS, platform engineering and DevOps experience. Exposure to regulated / validated environments such as GxP. Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life. For more information, visit .
08/06/2026
Full time
IDBS empowers BioPharma organizations to unlock the full potential of AI/ML to improve the lives and patient outcomes. As a trusted long-standing partner to 80% of the top 20 global BioPharma companies1, we deliver cloud-native software and services built specifically for the rapidly evolving needs of the industry. A Danaher company over 35 years of scientific informatics expertise, IDBS helps organizations design, execute and orchestrate processes; manage, contextualize and structure data; and gain valuable insights throughout the product lifecycle, from R&D through manufacturing. Widely recognised for our E-WorkBook platform, we've expanded our portfolio with flexible and scalable IDBSPolar and PIMS cloud platforms, enabling scientists to make smarter, faster decisions with confidence in both GxP and non-GxP environments. Do you want to work in a dynamic, fast paced, high performing, safe to fail and fun environment which is founded on trust, empowerment and autonomy? Do you enjoy solving complex customer problems as a team? What we'll get you doing: Lead cross-functional initiatives, supported by Engineering Director, to enhance quality, security, reliability and productivity. This includes championing best practices, strengthening data platform, integrating AI-driven tooling, and applying Agile ways of working to accelerate delivery. Champion a strong customer-focused culture by ensuring engineering decisions align with user needs, improve customer experience and deliver measurable value. Drive continuous improvement and innovation by optimising processes, reducing friction and raising engineering standards across the organization. Develop and coach your team to deliver high-quality software through guidance on modern engineering practices, architectural patterns and clean coding principles. Experience with Python, Java and frontend technologies like React is a plus. Grow and develop engineering talent through structured performance reviews, regular 1-2-1s, and clear personal development objectives. 21s, Strengthen collaboration and communication by working closely with Scrum Masters, Strategy, Product, Architecture, Quality and other key stakeholders. Instil a start-up mindset by promoting speed, ownership and experimentation to drive innovation and impactful delivery. What success looks like: Proven leadership in building highly engaged engineering teams that consistently deliver high quality software through strong management and Agile delivery practices. Effective people management grounded in active listening, supporting individual growth, and fostering diversity in a psychologically safe environment. Clear communication of technical concepts to both technical and nontechnical audiences. Consistent delivery of secure and high-quality engineering outcomes. Continuous improvement to drive delivery efficiency incrementally. Effective collaboration across cross functional teams to achieve aligned customer-focused results. A proactive, innovative mindset that embraces ownership, experimentation and modern engineering practices. Nice to have: Familiarity with AI driven engineering tools and data-centric development practices. Background in AWS, platform engineering and DevOps experience. Exposure to regulated / validated environments such as GxP. Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life. For more information, visit .
Senior Business Intelligence Engineer, Delivery Speed and Long-term Planning Job ID: Amazon EU SarL (GBP) - F16 Have you ever ordered a product on Amazon websites and wondered how it got delivered to you so fast, and what kinds of systems & processes are running behind the scenes to power the whole operation? If so, this role is for you! The team: Same Day Speed Data Operations is at the heart of the Amazon customer experience. Each action we undertake is on behalf of our customers, as surpassing their expectations is our passion. We improve customer experience through continuously optimizing the complex movements of goods from vendors to customers throughout Europe. Global transportation analytical teams are transversal centers of expertise, composed of engineers, analysts, scientists, technical program managers and developers. We are focused on Amazon most complex problems, processes and decisions. We work with fulfillment centers, transportation, software developers, finance and retail teams across the world, to improve our logistic infrastructure and algorithms. Fulfillment acceleration is one of those Global transportation analytical team. We are obsessed by rethinking our advanced end-to-end supply chain to make our deliveries even faster. Our overall mission is simple: we want Amazon to be the place where our customers can be delivered the next-day. Key job responsibilities This role will particularly suit someone with deep data engineering skills and an ability to navigate complex systems The role includes 80% analytical activities and 20% of stakeholder/project management. Innovation & Stakeholder/Project management: Use and share your insights with partner teams, to influence/build a 3 year roadmap of project to accelerate speed of deliveries Lead regular business review with partner teams to monitor the progress of projects in the roadmap. Consolidate progress into crisp and concise data-driven status updates. Data Analytics: Autonomously develop and lead design and execution of advanced metrics, reporting and bridging capabilities to support design speed strategy in Europe and North America Turn data into actionable business insights to improve complex tech systems in supply chain and work with partner teams to prioritize fixing system defects. Perform detailed data quality checks, proactively identifying and fixing data discrepancies and inaccuracies. Perform deep-dives and data analysis using SQL (>10TB) to uncover actionable insights for known and unknown problems. Provide recommendation on new metrics or business decision A day in the life An Amazon Business Intelligence Engineer starts the day by analyzing delivery speed data, collaborating with cross-functional teams to optimize processes. They create insightful reports and dashboards to aid decision-making for stakeholders like Operations and Logistics. By leveraging data science techniques, they forecast long-term trends to enhance delivery efficiency and customer satisfaction. They work closely with software developers, applying BI tools to improve system performance. Solving complex problems related to delivery speed and planning, they contribute to Amazon's goal of providing exceptional customer experiences. About the team GTS SLTP acts as the internal consulting team to help teams across Amazon achieves the right balance between customer experience and investments. Team members have a very large scope of impact and regularly interact with leadership two levels above them. Basic Qualifications Experience programming to extract, transform and clean large (multi-TB) data sets Experience with theory and practice of design of experiments and statistical analysis of results Experience with AWS technologies Experience in scripting for automation (e.g. Python) and advanced SQL skills. Experience with theory and practice of information retrieval, data science, machine learning and data mining Experience working directly with business stakeholders to translate between data and business needs Experience with SQL Experience with data visualization using Tableau, Quicksight, or similar tools Experience in the data/BI space Preferred Qualifications Experience managing, analyzing and communicating results to senior leadership Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
08/06/2026
Full time
Senior Business Intelligence Engineer, Delivery Speed and Long-term Planning Job ID: Amazon EU SarL (GBP) - F16 Have you ever ordered a product on Amazon websites and wondered how it got delivered to you so fast, and what kinds of systems & processes are running behind the scenes to power the whole operation? If so, this role is for you! The team: Same Day Speed Data Operations is at the heart of the Amazon customer experience. Each action we undertake is on behalf of our customers, as surpassing their expectations is our passion. We improve customer experience through continuously optimizing the complex movements of goods from vendors to customers throughout Europe. Global transportation analytical teams are transversal centers of expertise, composed of engineers, analysts, scientists, technical program managers and developers. We are focused on Amazon most complex problems, processes and decisions. We work with fulfillment centers, transportation, software developers, finance and retail teams across the world, to improve our logistic infrastructure and algorithms. Fulfillment acceleration is one of those Global transportation analytical team. We are obsessed by rethinking our advanced end-to-end supply chain to make our deliveries even faster. Our overall mission is simple: we want Amazon to be the place where our customers can be delivered the next-day. Key job responsibilities This role will particularly suit someone with deep data engineering skills and an ability to navigate complex systems The role includes 80% analytical activities and 20% of stakeholder/project management. Innovation & Stakeholder/Project management: Use and share your insights with partner teams, to influence/build a 3 year roadmap of project to accelerate speed of deliveries Lead regular business review with partner teams to monitor the progress of projects in the roadmap. Consolidate progress into crisp and concise data-driven status updates. Data Analytics: Autonomously develop and lead design and execution of advanced metrics, reporting and bridging capabilities to support design speed strategy in Europe and North America Turn data into actionable business insights to improve complex tech systems in supply chain and work with partner teams to prioritize fixing system defects. Perform detailed data quality checks, proactively identifying and fixing data discrepancies and inaccuracies. Perform deep-dives and data analysis using SQL (>10TB) to uncover actionable insights for known and unknown problems. Provide recommendation on new metrics or business decision A day in the life An Amazon Business Intelligence Engineer starts the day by analyzing delivery speed data, collaborating with cross-functional teams to optimize processes. They create insightful reports and dashboards to aid decision-making for stakeholders like Operations and Logistics. By leveraging data science techniques, they forecast long-term trends to enhance delivery efficiency and customer satisfaction. They work closely with software developers, applying BI tools to improve system performance. Solving complex problems related to delivery speed and planning, they contribute to Amazon's goal of providing exceptional customer experiences. About the team GTS SLTP acts as the internal consulting team to help teams across Amazon achieves the right balance between customer experience and investments. Team members have a very large scope of impact and regularly interact with leadership two levels above them. Basic Qualifications Experience programming to extract, transform and clean large (multi-TB) data sets Experience with theory and practice of design of experiments and statistical analysis of results Experience with AWS technologies Experience in scripting for automation (e.g. Python) and advanced SQL skills. Experience with theory and practice of information retrieval, data science, machine learning and data mining Experience working directly with business stakeholders to translate between data and business needs Experience with SQL Experience with data visualization using Tableau, Quicksight, or similar tools Experience in the data/BI space Preferred Qualifications Experience managing, analyzing and communicating results to senior leadership Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
08/06/2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
08/06/2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
08/06/2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
08/06/2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
08/06/2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
08/06/2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
