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Cambridge University Press & Assessment
Product Lead - Test Security
Cambridge University Press & Assessment
Job Title:   Product Lead - Test Security Salary:    £70,000 - £93,700 Location:   Cambridge, UK - Hybrid (2 days per week in the office) Contract:   Permanent Hours:   Full time 35 hours per week Deliver security‑focused product innovation that protects the integrity and global impact of the world's most trusted English test. We are Cambridge University Press & Assessment, a world‑leading academic publisher and assessment organisation, and a proud part of the University of Cambridge. We're looking for a strategic and impact‑driven   Product Lead – Test Security   to join our team. This is a rare opportunity to shape how we safeguard fairness and trust for millions of learners worldwide—while working at the forefront of emerging technologies, human behaviour, and global security threats.   About the role    As our Product Lead for Test Security, you will be accountable for setting and delivering the product strategy for how we detect, deter and prevent test malpractice within our assessment products. You will build the roadmap for critical security capabilities—ranging from AI‑enabled fraud detection and enhancements to response analytics—ensuring solutions are scalable, ethical, and aligned with the organisation's mission to protect the integrity of our tests. You'll work closely with colleagues across test security, engineering, data science, research, psychometrics, operations, legal and compliance to deliver high‑impact features that balance robust protection with excellent user experience. Additional responsibilities and accountabilities include: Translating emerging threats and business needs into clear, prioritised product requirements. Leading product discovery to validate the impact and feasibility of solutions.  Partnering with technical teams to deliver secure, resilient and high‑performing features such as anomaly detection models and identity verification workflows. Defining and tracking product success metrics, including security efficacy, false‑positive rates and user impact. Staying ahead of industry trends, fraud behaviours and evolving risks in the assessment and broader trust & safety landscape. Ensuring solutions comply with regulatory expectations and uphold fairness, transparency and responsible innovation principles. This position is hybrid, requiring 40–60% of your time on-site in Cambridge for collaboration and face‑to‑face connection. Flexible working requests will be considered from day one, including adjustments for candidates with disabilities or long‑term health conditions.     About You    You will bring strong experience in product management or an adjacent field (e.g., trust & safety, risk technology, security platforms) and can demonstrate: Proven success delivering complex, cross‑functional products or systems. Ability to navigate ambiguity, make informed trade-offs and drive strategic clarity. Confidence engaging with data, analytics, and emerging technologies such as machine learning or behavioural analytics. Strong communication skills, capable of influencing senior stakeholders and translating complexity into clear direction. Experience working in high‑integrity or compliance‑sensitive environments (e.g., assessments, fintech, security, identity, edtech) is highly advantageous. If you meet the above minimum criteria, we encourage you to apply. Your application will be even stronger if you can also demonstrate: Experience working in global or culturally diverse environments. A background in test security, fraud detection, identity verification or misuse prevention. Familiarity with psychometrics or assessment processes. Understanding of ethical AI, risk frameworks or responsible innovation principles. For a detailed job description, please refer to the link at the bottom of the advert on our careers site. We are a Disability Confident (DC) employer that is committed to equality and inclusion ensuring our recruitment process is accessible to all. The DC scheme's  Offer of an Interview  commitment applies to applicants who opt in, and disclose a disability or a long-term health condition, and best meet the minimum criteria for the role. In instances where interviewing all qualifying candidates is not practicable, we prioritise those who best meet the minimum criteria, as we would for applicants who do not have a disability or long-term health condition. Cambridge University Press & Assessment is an approved UK employer for the sponsorship of eligible roles and applicants under the Skilled Worker visa route. Please refer to the  gov.uk  website for guidance to understand your own eligibility based on the role you are applying for. Rewards and benefits     We will support you to be at your best in work and to live well outside of it. In addition to competitive salaries, we offer a world-class, flexible  rewards package , featuring family-friendly and planet-friendly benefits including:  28 days annual leave plus bank holidays  Private medical and Permanent Health Insurance   Discretionary annual bonus   Group personal pension scheme  Life assurance up to 4 x annual salary   Green travel schemes   Ready to pursue your potential? Apply now. We aim to support candidates by making our interview process clear and transparent. The closing date for all applications will be  5 February 2026.  We will review applications on an ongoing basis, and shortlisted candidates can expect interviews to take place from  12 – 18 February 2026 . If you are shortlisted and progressed through the stages, you can expect:  Virtual interview via MS Teams. You will be provided with a brief to complete a role related task which will need to be returned by email in advance of your interview.  Potentially a final stage interview: in-person at our offices in Cambridge. If you require any reasonable adjustments during the recruitment process due to a disability or a long-term health condition, there will be an opportunity for you to inform us via the online application form. We will do our best to accommodate your needs.   Please note that successful applicants will be subject to satisfactory background checks including DBS due to working in a regulated industry. We are committed to an equitable recruitment process. As such, applications must be submitted via our official online application procedure. Please refrain from sending your CV directly to our recruiters. If you experience technical difficulties or require additional support with submitting your online application, contact the Recruiter.  Why join us   Joining us is your opportunity to pursue potential. You will belong to a collaborative team that is exploring new and better ways to serve students, teachers and researchers across the globe – for the benefit of individuals, society and the world. Sharing our mission will inspire your own growth, development and progress, in an environment which embraces difference, change and aspiration. Cambridge University Press & Assessment is committed to being a place where anyone can enjoy a successful career, where it is safe to speak up, and where we learn continuously to improve together. We welcome applications from all candidates, regardless of demographic characteristics (age, disability, educational attainment, ethnicity, gender, marital status, neurodiversity, religion, sex, gender identity and sexual identity), cultural, or social class/background.    We believe better outcomes come through diversity of thought, background and approach. We welcome applications from people from all backgrounds and communities, actively seeking to employ people from a wide range of different communities.
23/01/2026
Full time
Job Title:   Product Lead - Test Security Salary:    £70,000 - £93,700 Location:   Cambridge, UK - Hybrid (2 days per week in the office) Contract:   Permanent Hours:   Full time 35 hours per week Deliver security‑focused product innovation that protects the integrity and global impact of the world's most trusted English test. We are Cambridge University Press & Assessment, a world‑leading academic publisher and assessment organisation, and a proud part of the University of Cambridge. We're looking for a strategic and impact‑driven   Product Lead – Test Security   to join our team. This is a rare opportunity to shape how we safeguard fairness and trust for millions of learners worldwide—while working at the forefront of emerging technologies, human behaviour, and global security threats.   About the role    As our Product Lead for Test Security, you will be accountable for setting and delivering the product strategy for how we detect, deter and prevent test malpractice within our assessment products. You will build the roadmap for critical security capabilities—ranging from AI‑enabled fraud detection and enhancements to response analytics—ensuring solutions are scalable, ethical, and aligned with the organisation's mission to protect the integrity of our tests. You'll work closely with colleagues across test security, engineering, data science, research, psychometrics, operations, legal and compliance to deliver high‑impact features that balance robust protection with excellent user experience. Additional responsibilities and accountabilities include: Translating emerging threats and business needs into clear, prioritised product requirements. Leading product discovery to validate the impact and feasibility of solutions.  Partnering with technical teams to deliver secure, resilient and high‑performing features such as anomaly detection models and identity verification workflows. Defining and tracking product success metrics, including security efficacy, false‑positive rates and user impact. Staying ahead of industry trends, fraud behaviours and evolving risks in the assessment and broader trust & safety landscape. Ensuring solutions comply with regulatory expectations and uphold fairness, transparency and responsible innovation principles. This position is hybrid, requiring 40–60% of your time on-site in Cambridge for collaboration and face‑to‑face connection. Flexible working requests will be considered from day one, including adjustments for candidates with disabilities or long‑term health conditions.     About You    You will bring strong experience in product management or an adjacent field (e.g., trust & safety, risk technology, security platforms) and can demonstrate: Proven success delivering complex, cross‑functional products or systems. Ability to navigate ambiguity, make informed trade-offs and drive strategic clarity. Confidence engaging with data, analytics, and emerging technologies such as machine learning or behavioural analytics. Strong communication skills, capable of influencing senior stakeholders and translating complexity into clear direction. Experience working in high‑integrity or compliance‑sensitive environments (e.g., assessments, fintech, security, identity, edtech) is highly advantageous. If you meet the above minimum criteria, we encourage you to apply. Your application will be even stronger if you can also demonstrate: Experience working in global or culturally diverse environments. A background in test security, fraud detection, identity verification or misuse prevention. Familiarity with psychometrics or assessment processes. Understanding of ethical AI, risk frameworks or responsible innovation principles. For a detailed job description, please refer to the link at the bottom of the advert on our careers site. We are a Disability Confident (DC) employer that is committed to equality and inclusion ensuring our recruitment process is accessible to all. The DC scheme's  Offer of an Interview  commitment applies to applicants who opt in, and disclose a disability or a long-term health condition, and best meet the minimum criteria for the role. In instances where interviewing all qualifying candidates is not practicable, we prioritise those who best meet the minimum criteria, as we would for applicants who do not have a disability or long-term health condition. Cambridge University Press & Assessment is an approved UK employer for the sponsorship of eligible roles and applicants under the Skilled Worker visa route. Please refer to the  gov.uk  website for guidance to understand your own eligibility based on the role you are applying for. Rewards and benefits     We will support you to be at your best in work and to live well outside of it. In addition to competitive salaries, we offer a world-class, flexible  rewards package , featuring family-friendly and planet-friendly benefits including:  28 days annual leave plus bank holidays  Private medical and Permanent Health Insurance   Discretionary annual bonus   Group personal pension scheme  Life assurance up to 4 x annual salary   Green travel schemes   Ready to pursue your potential? Apply now. We aim to support candidates by making our interview process clear and transparent. The closing date for all applications will be  5 February 2026.  We will review applications on an ongoing basis, and shortlisted candidates can expect interviews to take place from  12 – 18 February 2026 . If you are shortlisted and progressed through the stages, you can expect:  Virtual interview via MS Teams. You will be provided with a brief to complete a role related task which will need to be returned by email in advance of your interview.  Potentially a final stage interview: in-person at our offices in Cambridge. If you require any reasonable adjustments during the recruitment process due to a disability or a long-term health condition, there will be an opportunity for you to inform us via the online application form. We will do our best to accommodate your needs.   Please note that successful applicants will be subject to satisfactory background checks including DBS due to working in a regulated industry. We are committed to an equitable recruitment process. As such, applications must be submitted via our official online application procedure. Please refrain from sending your CV directly to our recruiters. If you experience technical difficulties or require additional support with submitting your online application, contact the Recruiter.  Why join us   Joining us is your opportunity to pursue potential. You will belong to a collaborative team that is exploring new and better ways to serve students, teachers and researchers across the globe – for the benefit of individuals, society and the world. Sharing our mission will inspire your own growth, development and progress, in an environment which embraces difference, change and aspiration. Cambridge University Press & Assessment is committed to being a place where anyone can enjoy a successful career, where it is safe to speak up, and where we learn continuously to improve together. We welcome applications from all candidates, regardless of demographic characteristics (age, disability, educational attainment, ethnicity, gender, marital status, neurodiversity, religion, sex, gender identity and sexual identity), cultural, or social class/background.    We believe better outcomes come through diversity of thought, background and approach. We welcome applications from people from all backgrounds and communities, actively seeking to employ people from a wide range of different communities.
AI Automation Engineer
McCabe & Barton
AI Automation Engineer | Hybrid 3 days a week in office | London | Permanent A leading financial services client in London is seeking a talented AI Automation Engineer to join their team. Please see below for key details. Role Overview: Analyse and optimise business processes for automation whilst designing, building, and deploying intelligent automation solutions using BPA platforms (Appian), Machine Learning, and Generative AI to drive operational efficiency and innovation. Key Characteristics: Process Analysis & Optimisation - Expert in analysing existing business processes through stakeholder interviews, process mapping, and workflow documentation to identify automation opportunities. Skilled in creating process flow diagrams, conducting time-motion studies, identifying bottlenecks and inefficiencies, and redesigning processes to be machine-readable and automation-ready using methodologies. Python Development - Strong proficiency in Python programming including object-oriented design, asynchronous programming, error handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including process modelling, interface design, expression rules, integration objects, and data modelling. Skilled in building end-to-end business process applications, configuring workflows, implementing business rules, managing records, and integrating Appian with external systems via REST APIs, web services, and connected systems. API Development & Integration - Proficient in designing and building RESTful APIs using FastAPI, Flask, or Django REST Framework for exposing AI models and automation services. Experience with API authentication (OAuth, JWT), rate limiting, error handling, API documentation (Swagger/OpenAPI), webhooks, and integrating disparate systems to create seamless automated workflows. Document Processing & OCR - Experience implementing intelligent document processing solutions using OCR technologies (Tesseract, Azure AI Document Intelligence, natural language processing for information extraction, document classification, and building end-to-end pipelines for automated document ingestion, processing, and data extraction with validation rules. Robotic Process Automation (RPA) - Knowledge of RPA concepts and tools (UiPath, Automation Anywhere, Power Automate) for automating repetitive tasks, screen scraping, and Legacy system integration. Ability to assess when RPA vs. API integration vs. AI solutions are most appropriate, and experience building hybrid automation solutions combining multiple technologies. Data Engineering & Pipeline Development - Strong skills in building data pipelines for AI/automation solutions including data extraction, transformation, and loading (ETL). Experience with SQL databases (SQL Server), data validation, cleansing workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing CI/CD pipelines for automated model training and deployment. Understanding of model governance, explainability, and compliance requirements. Solution Architecture & Technical Design - Ability to design end-to-end automation architectures that combine multiple technologies (BPA, ML, GenAI, APIs) into cohesive solutions. Experience creating technical design documents, system architecture diagrams, assessing build vs. buy decisions, estimating effort and complexity, and presenting technical recommendations to both technical and non-technical stakeholders. Stakeholder Collaboration & Change Management - Excellent communication skills for gathering requirements from business users, translating business needs into technical specifications, and demonstrating proof-of-concepts. Experience managing stakeholder expectations, conducting user acceptance testing, providing training on automated solutions, measuring automation ROI through KPIs (time saved, error reduction, cost savings), and driving adoption of intelligent automation across the organisation. If you align to the key requirements then please apply with an updated CV.
23/01/2026
Full time
AI Automation Engineer | Hybrid 3 days a week in office | London | Permanent A leading financial services client in London is seeking a talented AI Automation Engineer to join their team. Please see below for key details. Role Overview: Analyse and optimise business processes for automation whilst designing, building, and deploying intelligent automation solutions using BPA platforms (Appian), Machine Learning, and Generative AI to drive operational efficiency and innovation. Key Characteristics: Process Analysis & Optimisation - Expert in analysing existing business processes through stakeholder interviews, process mapping, and workflow documentation to identify automation opportunities. Skilled in creating process flow diagrams, conducting time-motion studies, identifying bottlenecks and inefficiencies, and redesigning processes to be machine-readable and automation-ready using methodologies. Python Development - Strong proficiency in Python programming including object-oriented design, asynchronous programming, error handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including process modelling, interface design, expression rules, integration objects, and data modelling. Skilled in building end-to-end business process applications, configuring workflows, implementing business rules, managing records, and integrating Appian with external systems via REST APIs, web services, and connected systems. API Development & Integration - Proficient in designing and building RESTful APIs using FastAPI, Flask, or Django REST Framework for exposing AI models and automation services. Experience with API authentication (OAuth, JWT), rate limiting, error handling, API documentation (Swagger/OpenAPI), webhooks, and integrating disparate systems to create seamless automated workflows. Document Processing & OCR - Experience implementing intelligent document processing solutions using OCR technologies (Tesseract, Azure AI Document Intelligence, natural language processing for information extraction, document classification, and building end-to-end pipelines for automated document ingestion, processing, and data extraction with validation rules. Robotic Process Automation (RPA) - Knowledge of RPA concepts and tools (UiPath, Automation Anywhere, Power Automate) for automating repetitive tasks, screen scraping, and Legacy system integration. Ability to assess when RPA vs. API integration vs. AI solutions are most appropriate, and experience building hybrid automation solutions combining multiple technologies. Data Engineering & Pipeline Development - Strong skills in building data pipelines for AI/automation solutions including data extraction, transformation, and loading (ETL). Experience with SQL databases (SQL Server), data validation, cleansing workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing CI/CD pipelines for automated model training and deployment. Understanding of model governance, explainability, and compliance requirements. Solution Architecture & Technical Design - Ability to design end-to-end automation architectures that combine multiple technologies (BPA, ML, GenAI, APIs) into cohesive solutions. Experience creating technical design documents, system architecture diagrams, assessing build vs. buy decisions, estimating effort and complexity, and presenting technical recommendations to both technical and non-technical stakeholders. Stakeholder Collaboration & Change Management - Excellent communication skills for gathering requirements from business users, translating business needs into technical specifications, and demonstrating proof-of-concepts. Experience managing stakeholder expectations, conducting user acceptance testing, providing training on automated solutions, measuring automation ROI through KPIs (time saved, error reduction, cost savings), and driving adoption of intelligent automation across the organisation. If you align to the key requirements then please apply with an updated CV.
Hays Specialist Recruitment Limited
Data Scientist
Hays Specialist Recruitment Limited
Data Scientist - MRO AI Solutions - £700+ per day inside IR35 (depending on experience) - Hybrid - 2-3 days per week in West Drayton or Paddington I am working with a key client within the Aviation Sector who are looking for a number of Data Scientists to join their team for an AI / Machine Learning Programme, working on Maintenance, Repair and Overhaul, improving systems and looking at automation. The project is estimated to last over two years, and will be offered in the form of a rolling 6 monthly contract, inside IR35. Role Purpose The Data ScientistS will develop advanced models and analytics to unlock value from operational data while ensuring solutions can be adapted for other OpCos. This role requires consultancy-level expertise in AI/ML and a strong ability to translate insights into business impact.Key Responsibilities Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modelling. Communicate findings and recommendations to business stakeholders. Continuously improve models based on feedback and operational performance. Develop models and analytics that can be generalised and adapted for different OpCos without extensive rework. Required Skills & Experience Proficiency in Python and ML frameworks (TensorFlow, PyTorch). Strong statistical and analytical skills. Experience with a wide range of Data Science techniques (e.g. ML, Optimisation, Simulation, GenAI, etc.). Demonstrated ability to take models from design through to production deployment, including performance optimisation, monitoring, and integration into business workflows beyond proof-of-concept or prototype stages. Familiarity with airline operations or supply chain analytics is desirable. Significant experience in similar roles, with a proven ability to integrate quickly into new teams and deliver immediate value. Initial co-location with BA teams in London is essential to ensure close collaboration. Candidates must also be prepared to travel internationally during later stages to facilitate group-wide deployment. Preferred Consulting-Level Competencies Ability to frame complex problems and deliver actionable solutions. Strong presentation and storytelling skills for executive audiences. Experience in high-impact consulting or transformation projects. Track record of creating high-impact outcomes and driving stakeholder satisfaction from day one. Experience in building reusable AI components and frameworks for enterprise-scale deployments. Candidates will require strong experience of roughly 5 years or more and will have stable CVs showing tenure in the companies they have worked in. Candidates from the Aviation industry are preferred, however excellent Data Scientists can be considered from similar sectors such as: Rail & Public Transport, Automotive & Commercial Fleets, Energy & Utilities, Oil & Gas / Petrochemical, Maritime & Shipping, Manufacturing / Industrial Machinery, Defence & Military, Space OMining & Heavy Equipment. Looking forward to receiving your application. Sponsorship is not provided for the role and I cannot accept directly sponsored candidates. Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at hays.co.uk
23/01/2026
Contractor
Data Scientist - MRO AI Solutions - £700+ per day inside IR35 (depending on experience) - Hybrid - 2-3 days per week in West Drayton or Paddington I am working with a key client within the Aviation Sector who are looking for a number of Data Scientists to join their team for an AI / Machine Learning Programme, working on Maintenance, Repair and Overhaul, improving systems and looking at automation. The project is estimated to last over two years, and will be offered in the form of a rolling 6 monthly contract, inside IR35. Role Purpose The Data ScientistS will develop advanced models and analytics to unlock value from operational data while ensuring solutions can be adapted for other OpCos. This role requires consultancy-level expertise in AI/ML and a strong ability to translate insights into business impact.Key Responsibilities Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modelling. Communicate findings and recommendations to business stakeholders. Continuously improve models based on feedback and operational performance. Develop models and analytics that can be generalised and adapted for different OpCos without extensive rework. Required Skills & Experience Proficiency in Python and ML frameworks (TensorFlow, PyTorch). Strong statistical and analytical skills. Experience with a wide range of Data Science techniques (e.g. ML, Optimisation, Simulation, GenAI, etc.). Demonstrated ability to take models from design through to production deployment, including performance optimisation, monitoring, and integration into business workflows beyond proof-of-concept or prototype stages. Familiarity with airline operations or supply chain analytics is desirable. Significant experience in similar roles, with a proven ability to integrate quickly into new teams and deliver immediate value. Initial co-location with BA teams in London is essential to ensure close collaboration. Candidates must also be prepared to travel internationally during later stages to facilitate group-wide deployment. Preferred Consulting-Level Competencies Ability to frame complex problems and deliver actionable solutions. Strong presentation and storytelling skills for executive audiences. Experience in high-impact consulting or transformation projects. Track record of creating high-impact outcomes and driving stakeholder satisfaction from day one. Experience in building reusable AI components and frameworks for enterprise-scale deployments. Candidates will require strong experience of roughly 5 years or more and will have stable CVs showing tenure in the companies they have worked in. Candidates from the Aviation industry are preferred, however excellent Data Scientists can be considered from similar sectors such as: Rail & Public Transport, Automotive & Commercial Fleets, Energy & Utilities, Oil & Gas / Petrochemical, Maritime & Shipping, Manufacturing / Industrial Machinery, Defence & Military, Space OMining & Heavy Equipment. Looking forward to receiving your application. Sponsorship is not provided for the role and I cannot accept directly sponsored candidates. Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at hays.co.uk
Data Engineer
Youngs Employment Services
Data Engineer - Hybrid - London / 2 or 3 days work from home Circ £55,000 - £70,000 + Excellent Benefits Package A fantastic opportunity is available for a Data Engineer that enjoys working in a fast paced and collaborative team playing work environment. Our client is a prestigious and successful ecommerce / wholesale business trading all over the globe. They've been expanding at a remarkable pace and as a consequence have transformed their technical landscape with leading edge solutions. Having implemented a new MS Fabric based Data platform, the need is now to scale up and deliver data driven insights and strategies right across the business globally. The Data Engineer will be joining a close knit friendly team that is the hub of our clients global data & analytics operation. The role would suit a mid-level data engineer, or a junior engineer with 2 years experience looking to take the next step up. Previous experience with MS Fabric would be beneficial but is by no means essential. Interested candidates must have experience in a similar role with MS Azure Data Platforms, Synapse, Databricks or other Cloud platforms such as AWS, GCP, Snowfake etc. Key Responsibilities will include; Design, implement, and optimize end-to-end solutions using Fabric components: o Data Factory (pipelines, orchestration) o Data Engineering (Lakehouse, notebooks, Apache Spark) o Data Warehouse (SQL endpoints, schemas, MPP performance tuning) o Real-Time Analytics (KQL databases, event ingestion) o Manage and enhance OneLake architecture, delta lake tables, security policies, and data governance within Fabric. o Build scalable, reusable data assets and engineering patterns that support analytics, reporting, and machine learning workloads. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver effective solutions. Troubleshoot and resolve data-related issues in a timely manner. Key Experience, Skills and Knowledge: Proven 2 yrs+ experience as a Data Engineer or similar role, with a strong focus on PySpark, SQL, Microsoft Azure Data platforms and Power BI an advantage Proficiency in development languages suitable for intermediate-level data engineers, such as: Python / PySpark: Widely used for data manipulation, analysis, and scripting. SQL: Essential for querying and managing relational databases. Understanding of D365 F&O Data Structures is highly desirable Strong problem-solving skills and attention to detail. Excellent communication and collaboration abilities. This is a hybrid role based in Central / West London with the flexibility to work from home 2 or 3 days per week. Salary will be dependent on experience and likely to be in the region of £55,000 - £70,000 + an attractive benefits package including bonus scheme. For further information, please send your CV to Wayne Young at Young's Employment Services Ltd. YES are operating as both a recruitment Agency and Recruitment Business
22/01/2026
Full time
Data Engineer - Hybrid - London / 2 or 3 days work from home Circ £55,000 - £70,000 + Excellent Benefits Package A fantastic opportunity is available for a Data Engineer that enjoys working in a fast paced and collaborative team playing work environment. Our client is a prestigious and successful ecommerce / wholesale business trading all over the globe. They've been expanding at a remarkable pace and as a consequence have transformed their technical landscape with leading edge solutions. Having implemented a new MS Fabric based Data platform, the need is now to scale up and deliver data driven insights and strategies right across the business globally. The Data Engineer will be joining a close knit friendly team that is the hub of our clients global data & analytics operation. The role would suit a mid-level data engineer, or a junior engineer with 2 years experience looking to take the next step up. Previous experience with MS Fabric would be beneficial but is by no means essential. Interested candidates must have experience in a similar role with MS Azure Data Platforms, Synapse, Databricks or other Cloud platforms such as AWS, GCP, Snowfake etc. Key Responsibilities will include; Design, implement, and optimize end-to-end solutions using Fabric components: o Data Factory (pipelines, orchestration) o Data Engineering (Lakehouse, notebooks, Apache Spark) o Data Warehouse (SQL endpoints, schemas, MPP performance tuning) o Real-Time Analytics (KQL databases, event ingestion) o Manage and enhance OneLake architecture, delta lake tables, security policies, and data governance within Fabric. o Build scalable, reusable data assets and engineering patterns that support analytics, reporting, and machine learning workloads. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver effective solutions. Troubleshoot and resolve data-related issues in a timely manner. Key Experience, Skills and Knowledge: Proven 2 yrs+ experience as a Data Engineer or similar role, with a strong focus on PySpark, SQL, Microsoft Azure Data platforms and Power BI an advantage Proficiency in development languages suitable for intermediate-level data engineers, such as: Python / PySpark: Widely used for data manipulation, analysis, and scripting. SQL: Essential for querying and managing relational databases. Understanding of D365 F&O Data Structures is highly desirable Strong problem-solving skills and attention to detail. Excellent communication and collaboration abilities. This is a hybrid role based in Central / West London with the flexibility to work from home 2 or 3 days per week. Salary will be dependent on experience and likely to be in the region of £55,000 - £70,000 + an attractive benefits package including bonus scheme. For further information, please send your CV to Wayne Young at Young's Employment Services Ltd. YES are operating as both a recruitment Agency and Recruitment Business
Michael Page
Data Scientist
Michael Page
Data Scientist / Machine Learning Engineer Join our team as a Data Scientist / Machine Learning expert in the Analytics department within the business services industry. This permanent position, based in London, offers an opportunity to apply advanced data science techniques to deliver actionable insights. Client Details Data Scientist / Machine Learning Engineer Our client is a well-established organisation within the business services industry. They are a medium-sized entity with a commitment to innovation and excellence in their field, providing a supportive environment for professional growth. Description Data Scientist / Machine Learning Engineer Develop and implement machine learning models to analyse complex data sets. Collaborate with cross-functional teams to identify business challenges and provide data-driven solutions. Optimise data pipelines and workflows for improved efficiency. Translate analytical findings into clear insights and recommendations for stakeholders. Stay updated on the latest advancements in data science and machine learning methodologies. Create and maintain detailed documentation of data models and processes. Conduct exploratory data analysis to uncover trends and patterns. Ensure data quality and integrity throughout all analytics processes. Profile Data Scientist / Machine Learning Engineer A successful Data Scientist / Machine Learning expert should have: A strong academic background in data science, computer science, mathematics, or a related field. Hands-on experience with AWS ML stack (SageMaker, Lambda, Redshift). Proven ability to design and implement machine learning algorithms and models. Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Strong data analysis, statistical modelling, and experimentation skills. Experience with data visualisation tools and techniques. Proficiency in programming languages such as Python, R, or similar. Knowledge of data processing frameworks and platforms. Attention to detail and a methodical approach to problem-solving. Job Offer Data Scientist / Machine Learning Engineer Competitive salary ranging from 60,000 to 69,000 per annum. Comprehensive standard benefits package. Opportunity to work in the thriving business services industry. Located in the heart of London with excellent transport links. Permanent role with opportunities for professional growth and development. If you are ready to take the next step in your career as a Data Scientist / Machine Learning specialist, we encourage you to apply now!
22/01/2026
Full time
Data Scientist / Machine Learning Engineer Join our team as a Data Scientist / Machine Learning expert in the Analytics department within the business services industry. This permanent position, based in London, offers an opportunity to apply advanced data science techniques to deliver actionable insights. Client Details Data Scientist / Machine Learning Engineer Our client is a well-established organisation within the business services industry. They are a medium-sized entity with a commitment to innovation and excellence in their field, providing a supportive environment for professional growth. Description Data Scientist / Machine Learning Engineer Develop and implement machine learning models to analyse complex data sets. Collaborate with cross-functional teams to identify business challenges and provide data-driven solutions. Optimise data pipelines and workflows for improved efficiency. Translate analytical findings into clear insights and recommendations for stakeholders. Stay updated on the latest advancements in data science and machine learning methodologies. Create and maintain detailed documentation of data models and processes. Conduct exploratory data analysis to uncover trends and patterns. Ensure data quality and integrity throughout all analytics processes. Profile Data Scientist / Machine Learning Engineer A successful Data Scientist / Machine Learning expert should have: A strong academic background in data science, computer science, mathematics, or a related field. Hands-on experience with AWS ML stack (SageMaker, Lambda, Redshift). Proven ability to design and implement machine learning algorithms and models. Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Strong data analysis, statistical modelling, and experimentation skills. Experience with data visualisation tools and techniques. Proficiency in programming languages such as Python, R, or similar. Knowledge of data processing frameworks and platforms. Attention to detail and a methodical approach to problem-solving. Job Offer Data Scientist / Machine Learning Engineer Competitive salary ranging from 60,000 to 69,000 per annum. Comprehensive standard benefits package. Opportunity to work in the thriving business services industry. Located in the heart of London with excellent transport links. Permanent role with opportunities for professional growth and development. If you are ready to take the next step in your career as a Data Scientist / Machine Learning specialist, we encourage you to apply now!
Trust In Soda
Python Software Engineer
Trust In Soda Cambridge, Cambridgeshire
Python Software Engineer - HIRING ASAP Start date: ASAP Duration: 12-month contract Location: 3 days in Cambridge, 2 days remote working Rate: £400 - £550 per day PAYE Summary The role is ideal for someone with an enterprise development background, with a strong technology, coding, and data skills, looking to operate in a less constrained environment, as part of an accelerated development team. The role is ideal for a skilled technical leader with strong design, teamwork and influencing skills. Ideally the candidate is a full stack, but this role will be primarily focused on processing and generating Analytics from structured and unstructured datasets with the ability of parallel processing potentially in the cloud. The successful candidate will have the opportunity to get exposure to prompt engineering for Large Language Models (LLMs) such as OpenAI's GPT-4 (ChatGPT), Google Gemini, and Anthropic Claude, with practical experience in designing, optimizing, and deploying AI/ML workflows in production environments to drive business value and innovation. Responsibilities Create robust, flexible, and scalable ML tooling and infrastructure which supports research scientists to leverage our clients' powerful infrastructure (through eg source control, distributed compute clusters, data storage). Work collaboratively as part of a multifunctional team where communication, documentation and teamwork are highly valued. Write clean, maintainable code, debug complex problems that span systems, prioritize ruthlessly, and get things done with a high level of efficiency. Coordinate with a large set of internal infrastructure and tool teams across the lab and across our client to evaluate and integrate with existing systems. Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR/VR problem solving. Key Skills Bachelor's degree in computer science or related field, or equivalent work experience. 4+ years industry experience with deep learning frameworks in Python, such as Pytorch or Tensorflow. 2+ years industry experience working with large, complex data sets for machine learning, including capture and annotation. Demonstrated experience implementing and evaluating working and end-to-end prototypical learning systems. Experience working with high performance or distributed compute solutions. Deployment and continuous integration experience. Familiarity with Machine Learning for Audio, multimodal or DSP purposes Experience writing scalable ML tooling/pipelines for use by researchers. Experience in Linux or Windows Shell Scripting. Ability to gather requirements and work closely with researchers to develop novel solutions. History of writing code to support the execution of research initiatives. Top 3 Skills We're looking for Python and infrastructure focused software engineers. ML Research. Engineering Mindset.
22/01/2026
Contractor
Python Software Engineer - HIRING ASAP Start date: ASAP Duration: 12-month contract Location: 3 days in Cambridge, 2 days remote working Rate: £400 - £550 per day PAYE Summary The role is ideal for someone with an enterprise development background, with a strong technology, coding, and data skills, looking to operate in a less constrained environment, as part of an accelerated development team. The role is ideal for a skilled technical leader with strong design, teamwork and influencing skills. Ideally the candidate is a full stack, but this role will be primarily focused on processing and generating Analytics from structured and unstructured datasets with the ability of parallel processing potentially in the cloud. The successful candidate will have the opportunity to get exposure to prompt engineering for Large Language Models (LLMs) such as OpenAI's GPT-4 (ChatGPT), Google Gemini, and Anthropic Claude, with practical experience in designing, optimizing, and deploying AI/ML workflows in production environments to drive business value and innovation. Responsibilities Create robust, flexible, and scalable ML tooling and infrastructure which supports research scientists to leverage our clients' powerful infrastructure (through eg source control, distributed compute clusters, data storage). Work collaboratively as part of a multifunctional team where communication, documentation and teamwork are highly valued. Write clean, maintainable code, debug complex problems that span systems, prioritize ruthlessly, and get things done with a high level of efficiency. Coordinate with a large set of internal infrastructure and tool teams across the lab and across our client to evaluate and integrate with existing systems. Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR/VR problem solving. Key Skills Bachelor's degree in computer science or related field, or equivalent work experience. 4+ years industry experience with deep learning frameworks in Python, such as Pytorch or Tensorflow. 2+ years industry experience working with large, complex data sets for machine learning, including capture and annotation. Demonstrated experience implementing and evaluating working and end-to-end prototypical learning systems. Experience working with high performance or distributed compute solutions. Deployment and continuous integration experience. Familiarity with Machine Learning for Audio, multimodal or DSP purposes Experience writing scalable ML tooling/pipelines for use by researchers. Experience in Linux or Windows Shell Scripting. Ability to gather requirements and work closely with researchers to develop novel solutions. History of writing code to support the execution of research initiatives. Top 3 Skills We're looking for Python and infrastructure focused software engineers. ML Research. Engineering Mindset.
Qualient Technology Solutions UK Limited
Senior Security Architect
Qualient Technology Solutions UK Limited
We at Qualient solutions looking for Senior Security Architect with Azure Cloud & Sentinel and Defender XDR implementation experience. Job Description:- We are seeking an experienced Senior Security Architect with deep expertise across enterprise security solutions and cloud security technologies. The ideal candidate will have a strong background in designing and implementing large-scale security architectures, advanced threat detection capabilities, and modern security analytics frameworks. This role requires exceptional communication skills, the ability to engage with both technical and executive stakeholders, and a strong understanding of cloud-native security solutions-particularly within the Azure ecosystem. Key Responsibilities Design and develop end-to-end enterprise security architectures, including infrastructure, data ingestion pipelines, and cloud security posture components. Lead the implementation and optimization of Microsoft security technologies such as Sentinel , Defender XDR , SOAR , and integrations involving DevOps (IDE/CI/CD) and Cribl . Develop advanced security analytics, threat intelligence models, and monitoring capabilities for cloud and hybrid environments. Work closely with engineering, DevOps, and security operations teams to ensure seamless security integration across platforms. Create architectural artifacts including high-level designs, solution diagrams, security models, and technical documentation. Communicate complex technical concepts to diverse audiences, including senior executives, technical teams, and business stakeholders. Provide advisory support on Azure Security, Data Ingest solutions, and Cloud Security Posture Management (CSPM). Drive continuous improvements, best practices, and innovation within the enterprise security architecture domain. Required Skills & Expertise Deep expertise in enterprise security technologies, especially: Microsoft Sentinel Defender XDR SOAR DevOps security (IDE/CI/CD) Cribl Strong hands-on experience with: Azure Security services Cloud Security Posture Management (CSPM) Data ingestion frameworks Security analytics and threat intelligence solutions Expertise in one or more specialized areas: Azure Data Factory Microsoft Sentinel Cybersecurity solutions SQL Machine Learning Exceptional communication and presentation skills, especially when working with executive leadership. Ability to translate technical concepts into business language and tailor messaging to diverse audiences. Experience designing and documenting comprehensive security architecture solutions. Qualifications & Experience Bachelor's degree in Computer Science or equivalent professional experience. 12+ years of experience in the Information Technology field. 5+ years of experience in architecture roles, including solution architecture. 3+ years of hands-on experience in enterprise security architecture. Professional security certifications such as CISSP , CISM , or Azure-focused security certifications (eg, AZ-500, SC-100).
22/01/2026
Full time
We at Qualient solutions looking for Senior Security Architect with Azure Cloud & Sentinel and Defender XDR implementation experience. Job Description:- We are seeking an experienced Senior Security Architect with deep expertise across enterprise security solutions and cloud security technologies. The ideal candidate will have a strong background in designing and implementing large-scale security architectures, advanced threat detection capabilities, and modern security analytics frameworks. This role requires exceptional communication skills, the ability to engage with both technical and executive stakeholders, and a strong understanding of cloud-native security solutions-particularly within the Azure ecosystem. Key Responsibilities Design and develop end-to-end enterprise security architectures, including infrastructure, data ingestion pipelines, and cloud security posture components. Lead the implementation and optimization of Microsoft security technologies such as Sentinel , Defender XDR , SOAR , and integrations involving DevOps (IDE/CI/CD) and Cribl . Develop advanced security analytics, threat intelligence models, and monitoring capabilities for cloud and hybrid environments. Work closely with engineering, DevOps, and security operations teams to ensure seamless security integration across platforms. Create architectural artifacts including high-level designs, solution diagrams, security models, and technical documentation. Communicate complex technical concepts to diverse audiences, including senior executives, technical teams, and business stakeholders. Provide advisory support on Azure Security, Data Ingest solutions, and Cloud Security Posture Management (CSPM). Drive continuous improvements, best practices, and innovation within the enterprise security architecture domain. Required Skills & Expertise Deep expertise in enterprise security technologies, especially: Microsoft Sentinel Defender XDR SOAR DevOps security (IDE/CI/CD) Cribl Strong hands-on experience with: Azure Security services Cloud Security Posture Management (CSPM) Data ingestion frameworks Security analytics and threat intelligence solutions Expertise in one or more specialized areas: Azure Data Factory Microsoft Sentinel Cybersecurity solutions SQL Machine Learning Exceptional communication and presentation skills, especially when working with executive leadership. Ability to translate technical concepts into business language and tailor messaging to diverse audiences. Experience designing and documenting comprehensive security architecture solutions. Qualifications & Experience Bachelor's degree in Computer Science or equivalent professional experience. 12+ years of experience in the Information Technology field. 5+ years of experience in architecture roles, including solution architecture. 3+ years of hands-on experience in enterprise security architecture. Professional security certifications such as CISSP , CISM , or Azure-focused security certifications (eg, AZ-500, SC-100).
Apex Resources Ltd
Machine Learning Engineer
Apex Resources Ltd
Apex Resources limited are on the lookout for a Machine Learning Engineer (Agentic AI) in Glasgow for a hybrid role. A leading Glasgow-based AI firm is building next-generation agentic AI products that automate complex tax and finance workflows for UK accountancy firms and in-house finance teams. The platform leverages large language models and intelligent orchestration to remove repetitive work and free specialists to focus on higher-value advice. The role You will join a small, high-calibre engineering team as an AI Developer, working on the core agentic AI platform for tax and finance automation. Day-to-day, you will design, build and ship production-grade features across the AI orchestration, reasoning and integration layers. Typical work includes: Designing and implementing agentic AI workflows that coordinate LLMs, tools and reasoning engines to handle end-to-end finance and tax processes. Building robust back-end services and APIs to support document ingestion, data extraction, multi-step reasoning and autonomous execution. Working with modern LLM tooling (advanced prompting, retrieval-augmented generation, tool calling, evaluation frameworks) to optimise accuracy, latency and reliability for real client workloads. Collaborating with product managers, domain SMEs (tax and finance) and fellow AI engineers to deliver features from concept through to production. Contributing to code quality, observability and secure engineering practices in a regulated, data-sensitive environment. Our tech stack You do not need experience with everything below, but you should be strong in several and able to learn the rest quickly. Languages: Python (core), plus exposure to TypeScript/JavaScript helpful for front-end integrations. AI & data: LLMs (OpenAI/Anthropic-style APIs), vector databases/RAG, agent frameworks, basic MLOps for deploying and monitoring AI systems in production. Orchestration: Workflow engines, event-driven architectures, multi-agent coordination systems. Cloud & infra: Azure or AWS, containerised services (Docker/Kubernetes), CI/CD pipelines and modern DevOps practices. Platform integrations: Connecting agentic AI to third-party tax/finance systems and APIs within customers existing tech stacks. What we re looking for Essential: 2+ years post-graduate experience as a Software Engineer / AI Engineer / ML Engineer working on production AI systems. Strong software engineering fundamentals: clean code, testing, version control and debugging in Python or similar. A Master s degree (or above) in Computer Science, Mathematics, AI/ML, Data Science, or a closely related discipline from a top-tier university. Demonstrable experience with applied AI/ML or LLM-based systems (projects, internships, or commercial work), not just academic exposure. Comfort working in a fast-moving, small-team environment where you take ownership from idea through to production release. Nice to have: Experience building agentic AI systems (tool-calling, multi-step planning, self-improvement loops) or autonomous agents. Knowledge of advanced agentic patterns and concepts like Model Context Protocol or similar orchestration standards. Exposure to financial, tax or accounting data and the nuances of working in regulated or data-sensitive environments. Why join? Direct impact: Ship agentic AI that immediately removes hours of manual work for tax and finance teams every day. Cutting-edge AI: Work at the forefront of agentic AI and enterprise-grade autonomous systems, delivering beyond proof-of-concepts. High-calibre team: Join experienced AI engineers shaping the future of finance automation with production-grade agentic technology. Growth opportunity: Be part of a scaling AI product business with room to shape technical direction and best practices. How to apply Send your CV to Chris at Apex Resources or call on (phone number removed)
22/01/2026
Seasonal
Apex Resources limited are on the lookout for a Machine Learning Engineer (Agentic AI) in Glasgow for a hybrid role. A leading Glasgow-based AI firm is building next-generation agentic AI products that automate complex tax and finance workflows for UK accountancy firms and in-house finance teams. The platform leverages large language models and intelligent orchestration to remove repetitive work and free specialists to focus on higher-value advice. The role You will join a small, high-calibre engineering team as an AI Developer, working on the core agentic AI platform for tax and finance automation. Day-to-day, you will design, build and ship production-grade features across the AI orchestration, reasoning and integration layers. Typical work includes: Designing and implementing agentic AI workflows that coordinate LLMs, tools and reasoning engines to handle end-to-end finance and tax processes. Building robust back-end services and APIs to support document ingestion, data extraction, multi-step reasoning and autonomous execution. Working with modern LLM tooling (advanced prompting, retrieval-augmented generation, tool calling, evaluation frameworks) to optimise accuracy, latency and reliability for real client workloads. Collaborating with product managers, domain SMEs (tax and finance) and fellow AI engineers to deliver features from concept through to production. Contributing to code quality, observability and secure engineering practices in a regulated, data-sensitive environment. Our tech stack You do not need experience with everything below, but you should be strong in several and able to learn the rest quickly. Languages: Python (core), plus exposure to TypeScript/JavaScript helpful for front-end integrations. AI & data: LLMs (OpenAI/Anthropic-style APIs), vector databases/RAG, agent frameworks, basic MLOps for deploying and monitoring AI systems in production. Orchestration: Workflow engines, event-driven architectures, multi-agent coordination systems. Cloud & infra: Azure or AWS, containerised services (Docker/Kubernetes), CI/CD pipelines and modern DevOps practices. Platform integrations: Connecting agentic AI to third-party tax/finance systems and APIs within customers existing tech stacks. What we re looking for Essential: 2+ years post-graduate experience as a Software Engineer / AI Engineer / ML Engineer working on production AI systems. Strong software engineering fundamentals: clean code, testing, version control and debugging in Python or similar. A Master s degree (or above) in Computer Science, Mathematics, AI/ML, Data Science, or a closely related discipline from a top-tier university. Demonstrable experience with applied AI/ML or LLM-based systems (projects, internships, or commercial work), not just academic exposure. Comfort working in a fast-moving, small-team environment where you take ownership from idea through to production release. Nice to have: Experience building agentic AI systems (tool-calling, multi-step planning, self-improvement loops) or autonomous agents. Knowledge of advanced agentic patterns and concepts like Model Context Protocol or similar orchestration standards. Exposure to financial, tax or accounting data and the nuances of working in regulated or data-sensitive environments. Why join? Direct impact: Ship agentic AI that immediately removes hours of manual work for tax and finance teams every day. Cutting-edge AI: Work at the forefront of agentic AI and enterprise-grade autonomous systems, delivering beyond proof-of-concepts. High-calibre team: Join experienced AI engineers shaping the future of finance automation with production-grade agentic technology. Growth opportunity: Be part of a scaling AI product business with room to shape technical direction and best practices. How to apply Send your CV to Chris at Apex Resources or call on (phone number removed)
Sky
Lead ML Engineer (Live Sports Insights)
Sky Hounslow, London
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Beckenham, Kent
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Hammersmith And Fulham, London
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Southall, Middlesex
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Merton, London
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Romford, Essex
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Wembley, Middlesex
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Islington, London
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Brent, London
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
Sky
Lead ML Engineer (Live Sports Insights)
Sky Stamford Hill, Cornwall
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.
22/01/2026
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. Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports-giving fans control, fresh perspectives, and predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable cloud b ased AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. What you'll bring Proven extensive lead level engineering experience delivering sports insights or sports data-driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. Experience designing scalable, low l atency architectures, including real time or near real time data processing (e.g., streaming systems) suitable for live or rapidly evolving sports use cases. Strong communication skills with the ability to inspire, guide, and clearly articulate complex strategies to executives, cross-functional teams, and stakeholders. 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.

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