Senior AI Researcher BeyondMath is a pioneering startup, backed by top-tier VCs, on a mission to reshape the frontiers of engineering through Foundational AI models for Physics. We are replacing traditional, slow and expensive simulation methods with AI that rivals accuracy at orders of magnitude higher speed. We are moving beyond the "generic AI" hype to solve the world's hardest physical engineering challenges in automotive, aerospace, and energy. We are looking for a Senior AI Researcher who balances scientific curiosity with the engineering discipline required to see models thrive in production environments. The Role As a Senior AI Researcher, you will be a core architect of our technical roadmap. This is not a "siloed" research role; you will lead the transition from theoretical breakthroughs in Physics based Deep Learning to robust, scalable systems used by world-class engineers. You will have the creative freedom to set research agendas while ensuring our models remain grounded in physical reality and industrial-scale performance. Key Responsibilities Architect Physics-AI Foundations: Lead the research and development of novel ML architectures (e.g., Transformers, GNNs, or Diffusion models) designed specifically to solve complex partial differential equations (PDEs) including aerodynamic simulations. Bridge Research & Production: Translate high-level mathematical concepts into clean, high-performance code. You won't just "throw models over the wall"; you will ensure they are optimized for inference and integrated into our production design platform. Advance Geometry Representation: Pioneer new ways to represent complex geometric design variations for efficient use in deep learning models. Strategic Leadership: Mentor junior researchers and engineers. Help define our internal research standards, reproducibility pipelines, and high-performance compute (HPC) infrastructure requirements. External Impact: Represent BeyondMath in the global AI community. Publish influential research at top-tier conferences (NeurIPS, ICML, ICLR) and position the company as the leader in "AI for Physics." Cross-Functional Collaboration: Partner with CFD specialists and software engineers to ensure our models respect physical constraints while maintaining thespeed advantages of neural networks. About You You are a rare hybrid: a scientist who loves the elegance of a theorem, but an engineer who gets a thrill from seeing a model successfully optimize a real-world turbine or airframe. You thrive in the ambiguity of a "greenfield" opportunity and have the grit to solve problems where no textbook solution exists. Essential Requirements: PhD or MSc in Computer Science, Physics, Mathematics, or a related quantitative field. 5+ years of post-grad experience in AI/ML research, with a demonstrable track record of models made it from the lab into production environments. Deep Technical Mastery: Expert-level proficiency in PyTorch, JAX, or TensorFlow, with a focus on building custom layers, loss functions, and optimization loops. Published Excellence: A strong record of high-quality publications in top-tier venues (e.g., NeurIPS, ICML, CVPR, or physics-specific AI journals). Systems Thinking: Experience with scalable training infrastructure, including distributed training across GPU clusters and data pipeline automation. Highly Desirable: Physics-ML Expertise: Experience with Physics-Informed Neural Networks (PINNs), Operator Learning (DeepONet/FNO), or Equivariant Neural Networks. Domain Knowledge: Familiarity with Aerodynamics, Fluid Dynamics, or Structural Mechanics. Engineering Rigor: Familiarity with C++, CUDA for low-level model optimization. Why Join Us? Full Ownership: You will have a direct seat at the table in shaping the future of a company redefining an entire industry. High Impact: Your work will directly accelerate the transition to sustainable energy and more efficient transport. Elite Team: Work alongside veterans from world-leading AI labs and engineering firms in a culture of "impact with integrity."
22/05/2026
Full time
Senior AI Researcher BeyondMath is a pioneering startup, backed by top-tier VCs, on a mission to reshape the frontiers of engineering through Foundational AI models for Physics. We are replacing traditional, slow and expensive simulation methods with AI that rivals accuracy at orders of magnitude higher speed. We are moving beyond the "generic AI" hype to solve the world's hardest physical engineering challenges in automotive, aerospace, and energy. We are looking for a Senior AI Researcher who balances scientific curiosity with the engineering discipline required to see models thrive in production environments. The Role As a Senior AI Researcher, you will be a core architect of our technical roadmap. This is not a "siloed" research role; you will lead the transition from theoretical breakthroughs in Physics based Deep Learning to robust, scalable systems used by world-class engineers. You will have the creative freedom to set research agendas while ensuring our models remain grounded in physical reality and industrial-scale performance. Key Responsibilities Architect Physics-AI Foundations: Lead the research and development of novel ML architectures (e.g., Transformers, GNNs, or Diffusion models) designed specifically to solve complex partial differential equations (PDEs) including aerodynamic simulations. Bridge Research & Production: Translate high-level mathematical concepts into clean, high-performance code. You won't just "throw models over the wall"; you will ensure they are optimized for inference and integrated into our production design platform. Advance Geometry Representation: Pioneer new ways to represent complex geometric design variations for efficient use in deep learning models. Strategic Leadership: Mentor junior researchers and engineers. Help define our internal research standards, reproducibility pipelines, and high-performance compute (HPC) infrastructure requirements. External Impact: Represent BeyondMath in the global AI community. Publish influential research at top-tier conferences (NeurIPS, ICML, ICLR) and position the company as the leader in "AI for Physics." Cross-Functional Collaboration: Partner with CFD specialists and software engineers to ensure our models respect physical constraints while maintaining thespeed advantages of neural networks. About You You are a rare hybrid: a scientist who loves the elegance of a theorem, but an engineer who gets a thrill from seeing a model successfully optimize a real-world turbine or airframe. You thrive in the ambiguity of a "greenfield" opportunity and have the grit to solve problems where no textbook solution exists. Essential Requirements: PhD or MSc in Computer Science, Physics, Mathematics, or a related quantitative field. 5+ years of post-grad experience in AI/ML research, with a demonstrable track record of models made it from the lab into production environments. Deep Technical Mastery: Expert-level proficiency in PyTorch, JAX, or TensorFlow, with a focus on building custom layers, loss functions, and optimization loops. Published Excellence: A strong record of high-quality publications in top-tier venues (e.g., NeurIPS, ICML, CVPR, or physics-specific AI journals). Systems Thinking: Experience with scalable training infrastructure, including distributed training across GPU clusters and data pipeline automation. Highly Desirable: Physics-ML Expertise: Experience with Physics-Informed Neural Networks (PINNs), Operator Learning (DeepONet/FNO), or Equivariant Neural Networks. Domain Knowledge: Familiarity with Aerodynamics, Fluid Dynamics, or Structural Mechanics. Engineering Rigor: Familiarity with C++, CUDA for low-level model optimization. Why Join Us? Full Ownership: You will have a direct seat at the table in shaping the future of a company redefining an entire industry. High Impact: Your work will directly accelerate the transition to sustainable energy and more efficient transport. Elite Team: Work alongside veterans from world-leading AI labs and engineering firms in a culture of "impact with integrity."
Synthesia is the world's leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. Senior Data Engineer We're hiring a Senior Data Engineer to join Synthesia and take ownership of our core data systems. You'll be responsible for designing and maintaining scalable pipelines, optimising data models, and ensuring high data quality and governance standards. What you'll do at Synthesia: Architect and scale robust, end-to-end data pipelines that ingest and transform complex semi-structured and structured data into our Snowflake data warehouse. Own the evolution of our dbt project - implementing modular modelling patterns and other best practices to ensure a "single source of truth" for the entire organisation. Manage platform infrastructure in Snowflake, AWS and other tools. Continuously optimise warehouse performance and cost by diagnosing bottlenecks, tuning inefficient queries, and improving how compute resources are used as we scale. Bridge the gap between experimental data science workflows and production, building the infrastructure and orchestration needed to deploy and monitor batch ML jobs. Drive best practices in data security, governance, and compliance, particularly with regards to AI. Partner with cross-functional stakeholders to understand data requirements and translate them into technical solutions. What we're looking for: 5+ years of experience as a Data Engineer or in a closely related role, with a proven track record of building and operating production data systems. Experience working in an early-stage or scaling data function. You're comfortable taking ownership and wearing multiple hats when needed. Strong foundations in software engineering and data modelling best practices, with an ability to design systems that are maintainable, scalable, and easy for others to build on. Deep expertise in SQL, and solid experience using Python or similar languages to build data pipelines, tooling, and orchestration (Airflow). Hands on experience managing cloud infrastructure using infrastructure-as-code (e.g. Terraform) on AWS, GCP, or similar platforms. A pragmatic approach to data platform design, with an eye for performance, cost efficiency, and operational reliability. Excellent communication skills: you can work effectively with technical and non-technical stakeholders to gather requirements, explain trade-offs and communicate data team needs. A product-oriented mindset, with an understanding of how data can shape decision making and accelerate company growth.
22/05/2026
Full time
Synthesia is the world's leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. Senior Data Engineer We're hiring a Senior Data Engineer to join Synthesia and take ownership of our core data systems. You'll be responsible for designing and maintaining scalable pipelines, optimising data models, and ensuring high data quality and governance standards. What you'll do at Synthesia: Architect and scale robust, end-to-end data pipelines that ingest and transform complex semi-structured and structured data into our Snowflake data warehouse. Own the evolution of our dbt project - implementing modular modelling patterns and other best practices to ensure a "single source of truth" for the entire organisation. Manage platform infrastructure in Snowflake, AWS and other tools. Continuously optimise warehouse performance and cost by diagnosing bottlenecks, tuning inefficient queries, and improving how compute resources are used as we scale. Bridge the gap between experimental data science workflows and production, building the infrastructure and orchestration needed to deploy and monitor batch ML jobs. Drive best practices in data security, governance, and compliance, particularly with regards to AI. Partner with cross-functional stakeholders to understand data requirements and translate them into technical solutions. What we're looking for: 5+ years of experience as a Data Engineer or in a closely related role, with a proven track record of building and operating production data systems. Experience working in an early-stage or scaling data function. You're comfortable taking ownership and wearing multiple hats when needed. Strong foundations in software engineering and data modelling best practices, with an ability to design systems that are maintainable, scalable, and easy for others to build on. Deep expertise in SQL, and solid experience using Python or similar languages to build data pipelines, tooling, and orchestration (Airflow). Hands on experience managing cloud infrastructure using infrastructure-as-code (e.g. Terraform) on AWS, GCP, or similar platforms. A pragmatic approach to data platform design, with an eye for performance, cost efficiency, and operational reliability. Excellent communication skills: you can work effectively with technical and non-technical stakeholders to gather requirements, explain trade-offs and communicate data team needs. A product-oriented mindset, with an understanding of how data can shape decision making and accelerate company growth.
Frontend Software Engineer - Simulation Workbench London, United Kingdom About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. The Role PhysicsX is developing a platform used by Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The core of this platform relies on handling massive volumes of complex simulation data, enabling high-fidelity multi-physics simulation through AI inference. We are looking for a Senior Frontend Software Engineer to join our product team. You will be one of a small team of Front-end Engineers, collaborating in a cross-functional team with autonomy to drive implementation decisions. You will build and evolve the frontend that brings our platform to life - from rich 3D visualisations of simulation data to seamless API integrations powering complex ML workflows. You will design composable frontend architectures, optimise performance for data-heavy interfaces, and ensure our engineers and scientists can interact intuitively with massive datasets and simulation results. As a senior engineer, you will also play a key role in shaping technical direction - authoring Technical Decision Records, mentoring less experienced engineers, and driving the standards that keep our platform reliable, secure, and performant. This is a role for a builder who loves crafting exceptional user experiences as much as they love designing robust frontend architectures. What You Will Do Build and evolve a frontend platform that supports complex simulation and ML workflows - from 3D visualisations to seamless API integrations and data-heavy interfaces. Design and implement composable frontend architectures and component systems, including micro-frontend patterns, to enable scalable and maintainable development. Optimise user experience through advanced caching strategies, performance monitoring, layout and paint optimisation, and accessibility best practices. Design and implement advanced state management and data flow patterns to handle the demands of real-time simulation data and complex user interactions. Own your work end-to-end - from architectural design through to deployment and maintenance in a fast-paced, agile environment. Define performance standards and SLAs for the services you own; diagnose and resolve complex performance bottlenecks in rendering, layout, and data handling. Collaborate with backend engineers on the implementation of security risk mitigation strategies and performance optimisations for frontend applications. Drive best practices in CI/CD, automated testing, observability, and infrastructure-as-code; build and maintain deployment pipelines including zero-downtime and multi-service deployments. Author and review Technical Decision Records; participate in Technology Radar reviews to evaluate and adopt new tools and approaches. Mentor junior engineers, facilitate technical discussions, build consensus around decisions, and translate research needs into well-defined technical requirements. What You Bring to the Table A passion for the craft - a drive for engineering excellence and a commitment to sponsoring that culture across the team. Architectural versatility - proven track record building web-based user interfaces using a variety of architectural approaches - SPAs, server-rendered applications, hybrid architectures, micro-frontends - with a critical perspective on when each is the right choice. Experience with React and TypeScript is expected, but your identity is not defined by them. API and data handling maturity - experience designing frontends that integrate with complex backends via REST, GraphQL, WebSockets, and SSE, with attention to caching strategies, data access patterns, and forward compatibility. Reliability and observability mindset - experience defining performance standards and SLAs, implementing monitoring/alerting, and optimising observability in production environments. Security and accessibility awareness - familiarity with OAuth/JWT, XSS/CSRF prevention, WCAG, and ARIA standards; experience collaborating with backend teams on security risk mitigation. CI/CD and deployment expertise - hands-on experience building and optimising CI/CD pipelines (e.g. NX, GitHub Actions, monorepos), including multi-service and zero-downtime deployment strategies. Data visualisation experience - building rich, interactive visualisations using libraries such as Plotly, ECharts, Three.js, VTK, or WebGL to expose complex simulation data to end-users. Diagnostic and optimisation skills - a proactive mindset with the ability to identify and resolve complex performance bottlenecks from first principles - in rendering, networking, and data processing - rather than relying on framework-level fixes. Communication and leadership - excellent communication skills to discuss data needs with research scientists and translate them into technical specifications. Experience mentoring engineers and facilitating technical decisions. Ideally 3D and GPU Technologies: deep experience with WebGL, WebGPU, or WebAssembly for high-performance rendering of simulation data, meshes, and point clouds. Advanced Testing Techniques: experience with fuzzing, deterministic simulation testing, or fault injection in production systems; strong foundation in E2E and integration testing across different architectural patterns. Domain Knowledge: understanding of 3D geometry processing (meshes, point clouds) and the specific data structures used in physics-based simulations. What We Offer Equity options - share in our success and growth. 10% employer pension contribution - invest in your future. Free office lunches - great food to fuel your workdays. Flexible working - balance your work and life in a way that works for you. Hybrid setup - enjoy our new Shoreditch office while keeping remote flexibility. Enhanced parental leave - support for life's biggest milestones. Private healthcare - comprehensive coverage. Personal development - access learning and training to help you grow. Work from anywhere - extend your remote setup to enjoy the sun or reconnect with loved ones. We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application. Apply for this job indicates a required field First Name Last Name Preferred First Name Email Phone Country Phone Location (City) Resume/CV Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf Website LinkedIn Profile Where did you hear about us? Select What is your notice period/when is the earliest you could start? Do you require Visa sponsorship to work in the role location? Select Please share your salary expectations: We collect diversity and inclusion data solely for the purposes of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.How would you describe your ethnicity? Select Do you have a disability or chronic condition (physical, visual, auditory, cognitive, mental, emotional, or other) that substantially limits one or more of your major life activities, including mobility, communication (seeing, hearing, speaking), and learning? Select How would you describe your gender identity? (mark all that apply) Select What interests you in Delivery at PhysicsX?
22/05/2026
Full time
Frontend Software Engineer - Simulation Workbench London, United Kingdom About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. The Role PhysicsX is developing a platform used by Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The core of this platform relies on handling massive volumes of complex simulation data, enabling high-fidelity multi-physics simulation through AI inference. We are looking for a Senior Frontend Software Engineer to join our product team. You will be one of a small team of Front-end Engineers, collaborating in a cross-functional team with autonomy to drive implementation decisions. You will build and evolve the frontend that brings our platform to life - from rich 3D visualisations of simulation data to seamless API integrations powering complex ML workflows. You will design composable frontend architectures, optimise performance for data-heavy interfaces, and ensure our engineers and scientists can interact intuitively with massive datasets and simulation results. As a senior engineer, you will also play a key role in shaping technical direction - authoring Technical Decision Records, mentoring less experienced engineers, and driving the standards that keep our platform reliable, secure, and performant. This is a role for a builder who loves crafting exceptional user experiences as much as they love designing robust frontend architectures. What You Will Do Build and evolve a frontend platform that supports complex simulation and ML workflows - from 3D visualisations to seamless API integrations and data-heavy interfaces. Design and implement composable frontend architectures and component systems, including micro-frontend patterns, to enable scalable and maintainable development. Optimise user experience through advanced caching strategies, performance monitoring, layout and paint optimisation, and accessibility best practices. Design and implement advanced state management and data flow patterns to handle the demands of real-time simulation data and complex user interactions. Own your work end-to-end - from architectural design through to deployment and maintenance in a fast-paced, agile environment. Define performance standards and SLAs for the services you own; diagnose and resolve complex performance bottlenecks in rendering, layout, and data handling. Collaborate with backend engineers on the implementation of security risk mitigation strategies and performance optimisations for frontend applications. Drive best practices in CI/CD, automated testing, observability, and infrastructure-as-code; build and maintain deployment pipelines including zero-downtime and multi-service deployments. Author and review Technical Decision Records; participate in Technology Radar reviews to evaluate and adopt new tools and approaches. Mentor junior engineers, facilitate technical discussions, build consensus around decisions, and translate research needs into well-defined technical requirements. What You Bring to the Table A passion for the craft - a drive for engineering excellence and a commitment to sponsoring that culture across the team. Architectural versatility - proven track record building web-based user interfaces using a variety of architectural approaches - SPAs, server-rendered applications, hybrid architectures, micro-frontends - with a critical perspective on when each is the right choice. Experience with React and TypeScript is expected, but your identity is not defined by them. API and data handling maturity - experience designing frontends that integrate with complex backends via REST, GraphQL, WebSockets, and SSE, with attention to caching strategies, data access patterns, and forward compatibility. Reliability and observability mindset - experience defining performance standards and SLAs, implementing monitoring/alerting, and optimising observability in production environments. Security and accessibility awareness - familiarity with OAuth/JWT, XSS/CSRF prevention, WCAG, and ARIA standards; experience collaborating with backend teams on security risk mitigation. CI/CD and deployment expertise - hands-on experience building and optimising CI/CD pipelines (e.g. NX, GitHub Actions, monorepos), including multi-service and zero-downtime deployment strategies. Data visualisation experience - building rich, interactive visualisations using libraries such as Plotly, ECharts, Three.js, VTK, or WebGL to expose complex simulation data to end-users. Diagnostic and optimisation skills - a proactive mindset with the ability to identify and resolve complex performance bottlenecks from first principles - in rendering, networking, and data processing - rather than relying on framework-level fixes. Communication and leadership - excellent communication skills to discuss data needs with research scientists and translate them into technical specifications. Experience mentoring engineers and facilitating technical decisions. Ideally 3D and GPU Technologies: deep experience with WebGL, WebGPU, or WebAssembly for high-performance rendering of simulation data, meshes, and point clouds. Advanced Testing Techniques: experience with fuzzing, deterministic simulation testing, or fault injection in production systems; strong foundation in E2E and integration testing across different architectural patterns. Domain Knowledge: understanding of 3D geometry processing (meshes, point clouds) and the specific data structures used in physics-based simulations. What We Offer Equity options - share in our success and growth. 10% employer pension contribution - invest in your future. Free office lunches - great food to fuel your workdays. Flexible working - balance your work and life in a way that works for you. Hybrid setup - enjoy our new Shoreditch office while keeping remote flexibility. Enhanced parental leave - support for life's biggest milestones. Private healthcare - comprehensive coverage. Personal development - access learning and training to help you grow. Work from anywhere - extend your remote setup to enjoy the sun or reconnect with loved ones. We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application. Apply for this job indicates a required field First Name Last Name Preferred First Name Email Phone Country Phone Location (City) Resume/CV Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf Website LinkedIn Profile Where did you hear about us? Select What is your notice period/when is the earliest you could start? Do you require Visa sponsorship to work in the role location? Select Please share your salary expectations: We collect diversity and inclusion data solely for the purposes of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.How would you describe your ethnicity? Select Do you have a disability or chronic condition (physical, visual, auditory, cognitive, mental, emotional, or other) that substantially limits one or more of your major life activities, including mobility, communication (seeing, hearing, speaking), and learning? Select How would you describe your gender identity? (mark all that apply) Select What interests you in Delivery at PhysicsX?
London Stock Exchange Group
Nottingham, Nottinghamshire
Principal Data Architect page is loaded Principal Data Architectlocations: GBR-Nottingham-1 Chapel Qtrtime type: Full timeposted on: Posted Todayjob requisition id: RLSEG (London Stock Exchange Group) is more than a diversified global financial markets infrastructure and data business. We are dedicated, open-access partners with a dedication to excellence in delivering the services our customers expect from us. With extensive experience, deep knowledge and worldwide presence across financial markets, we enable businesses and economies around the world to fund innovation, manage risk and create jobs. It's how we've contributed to supporting the financial stability and growth of communities and economies globally for more than 300 years. Through a comprehensive suite of trusted financial market infrastructure services - and our open-access model - we provide the flexibility, stability and trust that enable our customers to pursue their ambitions with confidence and clarity.LSEG is headquartered in the United Kingdom, with significant operations in 70 countries across EMEA, North America, Latin America and Asia Pacific. We employ 25,000 people globally, more than half located in Asia Pacific. LSEG's ticker symbol is LSEG. OUR PEOPLE: People are at the heart of what we do and drive the success of our business. Our culture of connecting, creating opportunity and delivering excellence shape how we think, how we do things and how we help our people fulfil their potential. We embrace diversity and actively seek to attract individuals with unique backgrounds and perspectives. We break down barriers and encourage teamwork, enabling innovation and rapid development of solutions that make a difference. Our workplace generates an enriching and rewarding experience for our people and customers alike. Our vision is to build an inclusive culture in which everyone feels encouraged to fulfil their potential.We know that real personal growth cannot be achieved by simply climbing a career ladder - which is why we encourage and enable a wealth of avenues and interesting opportunities for everyone to broaden and deepen their skills and expertise. As a global organisation spanning 70 countries and one rooted in a culture of growth, opportunity, diversity and innovation, LSEG is a place where everyone can grow, develop and fulfil your potential with meaningful careers. ROLE SUMMARY: Own the end-to-end data architecture for the Active Data Layer (ADL) programme across LSEG Risk Intelligence Engineering. Define and evolve the data flows, data models, integration patterns, and data assurance architecture that underpin World-Check's full data lifecycle, from acquisition, through curation, to distribution.Drive the data assurance strategy, embedding architectural foundations for data quality, lineage, and governance into ADL from the ground up. Partner with the AI Practice Lead to ensure data architecture enables safe, scalable adoption of AI and agentic capabilities. This is a senior IC role leading through influence and deep technical expertise. WHAT YOU'LL BE DOING: Data Architecture & Data Flows Own the end-to-end data architecture for ADL: target-state designs, canonical data models, data flow patterns, and platform standards across World-Check's full data lifecycle. Architect data flows between legacy systems, the new curation platform, and customer-facing distribution channels, ensuring traceability, consistency, and completeness. Design the data migration architecture from legacy to the new platform, ensuring data preservation, field mapping correctness, and schema integrity. Define event-driven data flow patterns for real-time propagation, including event schemas, ordering guarantees, and idempotency. Evaluate and recommend data technologies (event streaming, graph databases, data lakes, lakehouses) appropriate to ADL requirements.Data Assurance & Quality Drive the data assurance strategy within ADL, translating preventive, detective, and corrective control frameworks into architectural components. Design data lineage and provenance infrastructure enabling end-to-end traceability from source through curation to publication. Architect data contract and schema governance across pipeline boundaries, structurally enforcing schema conformity and API contract compliance. Define the data quality measurement architecture: where quality dimensions are measured, how thresholds are evaluated, and how results feed dashboards. Design reconciliation architecture supporting regression testing in non-production and continuous reconciliation in production. Architect test data management: synthetic data for development, production-representative data for testing, and golden datasets for regression.AI & Agentic Data Enablement Design data pipelines, feature stores, and access patterns for AI/ML model training, evaluation, and serving. Architect data foundations for agentic curation: data contracts, schema validation, and lineage capture at agent boundaries. Design AI evaluation infrastructure: golden dataset storage, semantic comparison pipelines, and confidence calibration measurement. Define data contract and versioning standards supporting rapid AI experimentation with production-grade reliability.Data Modelling, Governance & Platform Lead conceptual, logical, and physical data model design for ADL domains (screening, due diligence, entity resolution, adverse media). Partner with data governance and compliance teams to embed data ownership, classification, lineage, and access control into the architecture. Architect observability, monitoring, and alerting for production data quality: freshness, completeness, schema drift, and anomaly detection. Provide architectural guidance on cloud-native data services, storage strategies, compute scaling, and cost optimisation.Technical Leadership Act as the senior technical voice for data architecture across ADL, translating complex concepts into clear recommendations for engineering, product, and business stakeholders. Partner with the AI Practice Lead on feasibility, dependencies, risks, and sequencing for AI initiatives. Mentor engineers and data professionals on data modelling, data flow design, and assurance best practices. WHAT YOU'LL BRING: Qualifications & Experience 10+ years in data architecture or data engineering in complex, large-scale environments; 5+ years in a senior/lead architect capacity. Proven experience designing end-to-end data architectures supporting AI/ML, analytics, and real-time data products. Deep hands-on experience with modern data platforms (e.g., Snowflake, Databricks, Spark, Kafka, Elasticsearch, graph databases, AWS/Azure/GCP). Experience designing data quality and assurance frameworks: data lineage, data contracts, reconciliation, and quality measurement at scale. Background in financial services, risk, compliance, or highly regulated data-intensive environments (preferred). Experience with large-scale data migration programmes and legacy-to-modern platform transitions (preferred).Skills & Knowledge Data Architecture: Data modelling (conceptual, logical, physical), data flow design, event-driven architectures, integration patterns. Data Assurance & Quality: Data lineage, provenance, data contracts, reconciliation, and quality controls embedded across pipelines. AI/ML Data Foundations: Feature stores, ML pipelines, vector databases, embeddings, and data requirements for LLM/agentic systems. Cloud & Platform: Cloud-native data services, infrastructure-as-code, scalable platform patterns. Communication & Influence: Articulating complex decisions to technical and non-technical audiences; influencing without authority.Nice to Have Knowledge graphs, entity resolution, or graph-based models in risk, compliance, or financial crime domains. MLOps/LLMOps
22/05/2026
Full time
Principal Data Architect page is loaded Principal Data Architectlocations: GBR-Nottingham-1 Chapel Qtrtime type: Full timeposted on: Posted Todayjob requisition id: RLSEG (London Stock Exchange Group) is more than a diversified global financial markets infrastructure and data business. We are dedicated, open-access partners with a dedication to excellence in delivering the services our customers expect from us. With extensive experience, deep knowledge and worldwide presence across financial markets, we enable businesses and economies around the world to fund innovation, manage risk and create jobs. It's how we've contributed to supporting the financial stability and growth of communities and economies globally for more than 300 years. Through a comprehensive suite of trusted financial market infrastructure services - and our open-access model - we provide the flexibility, stability and trust that enable our customers to pursue their ambitions with confidence and clarity.LSEG is headquartered in the United Kingdom, with significant operations in 70 countries across EMEA, North America, Latin America and Asia Pacific. We employ 25,000 people globally, more than half located in Asia Pacific. LSEG's ticker symbol is LSEG. OUR PEOPLE: People are at the heart of what we do and drive the success of our business. Our culture of connecting, creating opportunity and delivering excellence shape how we think, how we do things and how we help our people fulfil their potential. We embrace diversity and actively seek to attract individuals with unique backgrounds and perspectives. We break down barriers and encourage teamwork, enabling innovation and rapid development of solutions that make a difference. Our workplace generates an enriching and rewarding experience for our people and customers alike. Our vision is to build an inclusive culture in which everyone feels encouraged to fulfil their potential.We know that real personal growth cannot be achieved by simply climbing a career ladder - which is why we encourage and enable a wealth of avenues and interesting opportunities for everyone to broaden and deepen their skills and expertise. As a global organisation spanning 70 countries and one rooted in a culture of growth, opportunity, diversity and innovation, LSEG is a place where everyone can grow, develop and fulfil your potential with meaningful careers. ROLE SUMMARY: Own the end-to-end data architecture for the Active Data Layer (ADL) programme across LSEG Risk Intelligence Engineering. Define and evolve the data flows, data models, integration patterns, and data assurance architecture that underpin World-Check's full data lifecycle, from acquisition, through curation, to distribution.Drive the data assurance strategy, embedding architectural foundations for data quality, lineage, and governance into ADL from the ground up. Partner with the AI Practice Lead to ensure data architecture enables safe, scalable adoption of AI and agentic capabilities. This is a senior IC role leading through influence and deep technical expertise. WHAT YOU'LL BE DOING: Data Architecture & Data Flows Own the end-to-end data architecture for ADL: target-state designs, canonical data models, data flow patterns, and platform standards across World-Check's full data lifecycle. Architect data flows between legacy systems, the new curation platform, and customer-facing distribution channels, ensuring traceability, consistency, and completeness. Design the data migration architecture from legacy to the new platform, ensuring data preservation, field mapping correctness, and schema integrity. Define event-driven data flow patterns for real-time propagation, including event schemas, ordering guarantees, and idempotency. Evaluate and recommend data technologies (event streaming, graph databases, data lakes, lakehouses) appropriate to ADL requirements.Data Assurance & Quality Drive the data assurance strategy within ADL, translating preventive, detective, and corrective control frameworks into architectural components. Design data lineage and provenance infrastructure enabling end-to-end traceability from source through curation to publication. Architect data contract and schema governance across pipeline boundaries, structurally enforcing schema conformity and API contract compliance. Define the data quality measurement architecture: where quality dimensions are measured, how thresholds are evaluated, and how results feed dashboards. Design reconciliation architecture supporting regression testing in non-production and continuous reconciliation in production. Architect test data management: synthetic data for development, production-representative data for testing, and golden datasets for regression.AI & Agentic Data Enablement Design data pipelines, feature stores, and access patterns for AI/ML model training, evaluation, and serving. Architect data foundations for agentic curation: data contracts, schema validation, and lineage capture at agent boundaries. Design AI evaluation infrastructure: golden dataset storage, semantic comparison pipelines, and confidence calibration measurement. Define data contract and versioning standards supporting rapid AI experimentation with production-grade reliability.Data Modelling, Governance & Platform Lead conceptual, logical, and physical data model design for ADL domains (screening, due diligence, entity resolution, adverse media). Partner with data governance and compliance teams to embed data ownership, classification, lineage, and access control into the architecture. Architect observability, monitoring, and alerting for production data quality: freshness, completeness, schema drift, and anomaly detection. Provide architectural guidance on cloud-native data services, storage strategies, compute scaling, and cost optimisation.Technical Leadership Act as the senior technical voice for data architecture across ADL, translating complex concepts into clear recommendations for engineering, product, and business stakeholders. Partner with the AI Practice Lead on feasibility, dependencies, risks, and sequencing for AI initiatives. Mentor engineers and data professionals on data modelling, data flow design, and assurance best practices. WHAT YOU'LL BRING: Qualifications & Experience 10+ years in data architecture or data engineering in complex, large-scale environments; 5+ years in a senior/lead architect capacity. Proven experience designing end-to-end data architectures supporting AI/ML, analytics, and real-time data products. Deep hands-on experience with modern data platforms (e.g., Snowflake, Databricks, Spark, Kafka, Elasticsearch, graph databases, AWS/Azure/GCP). Experience designing data quality and assurance frameworks: data lineage, data contracts, reconciliation, and quality measurement at scale. Background in financial services, risk, compliance, or highly regulated data-intensive environments (preferred). Experience with large-scale data migration programmes and legacy-to-modern platform transitions (preferred).Skills & Knowledge Data Architecture: Data modelling (conceptual, logical, physical), data flow design, event-driven architectures, integration patterns. Data Assurance & Quality: Data lineage, provenance, data contracts, reconciliation, and quality controls embedded across pipelines. AI/ML Data Foundations: Feature stores, ML pipelines, vector databases, embeddings, and data requirements for LLM/agentic systems. Cloud & Platform: Cloud-native data services, infrastructure-as-code, scalable platform patterns. Communication & Influence: Articulating complex decisions to technical and non-technical audiences; influencing without authority.Nice to Have Knowledge graphs, entity resolution, or graph-based models in risk, compliance, or financial crime domains. MLOps/LLMOps
About Us: Solirius Reply, part of the Reply Group, delivers technical consultancy and application delivery to our clients in order to solve real world problems and allow our clients to respond to an ever changing technical landscape. We partner closely with our clients, embedding our consultants into their businesses in order to provide a bespoke service, allowing us to truly understand our clients' needs. It is this close collaboration with our clients that has enabled us to grow rapidly in recent years and will drive our ambitious future growth plans. We currently have over 300 consultants working with a variety of key clients from both the public and private sectors such as the Ministry of Justice, Department for Education, FCDOS, UEFA, International Olympic Committee and Mercedes Benz; with plans to increase our client base further in the near future. We operate as a flat organisation and believe in trusting and supporting our team to operate independently. We pride ourselves on being specialists at what we do, making the most of our consultants' expertise in their fields in order to provide a best in class service to our clients. All our consultants have the opportunity to work on a range of different projects, providing a broad range of knowledge on which to develop their careers and progress in the direction they choose. About You: You are a motivated and adaptable professional with a strong analytical mindset and a passion for using technology to solve real world problems. You enjoy working in collaborative, agile teams and take pride in delivering high quality solutions that make a tangible impact. With strong communication skills and a consultative approach, you're comfortable engaging with clients, understanding their needs, and translating them into effective outcomes. You understand and align with Solirius Reply Values The Role: We are seeking a highly skilled Java Engineer with AI expertise to design, develop, and deploy intelligent, scalable applications. You will work at the intersection of backend engineering and artificial intelligence, building systems that integrate machine learning models, data pipelines, and cloud native services. This role is ideal for someone passionate about clean architecture, performance optimization, and applying AI technologies to real world business challenges. Key Responsibilities Design, develop, and maintain high-performance Java based applications Integrate AI/ML models into production grade backend systems Build RESTful APIs and microservices using modern Java frameworks Collaborate with data scientists to deploy and scale machine learning solutions Optimise system performance, scalability, and security Implement CI/CD pipelines and ensure high code quality standards Work with cloud platforms to deploy AI powered services Contribute to architecture decisions and technical roadmaps Required Qualifications Strong experience with Java 12+, Spring Boot, and microservices architecture Experience integrating AI/ML solutions into backend systems Understanding of REST APIs, distributed systems, and database design Familiarity with SQL and NoSQL databases Experience with cloud platforms (e.g., Amazon Web Services, Google Cloud Platform, or Microsoft Azure) Knowledge of containerisation technologies like Docker and orchestration tools such as Kubernetes Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java based ML libraries) Strong problem solving and communication skills Preferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with MLOps practices and model lifecycle management Knowledge of event driven architectures (Kafka or similar) Experience with DevOps tooling and infrastructure as code Exposure to Generative AI and large language models What We Offer: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development training per year Enhanced Parental Leave Paid Fertility Leave (5 Days) Statutory & Contributory Pension EAP with Gym Membership Benefits Flexible Working Annual Away Days/Company Socials Equality & Diversity: Solirius Reply is an equal opportunities employer. We are committed to creating a work environment that supports, celebrates, encourages, and respects all individuals and in which all processes are based on merit, competence and business needs. We do not discriminate on the basis of race, religion, gender, sexuality, age, disability, ethnicity, marital status or any other protected characteristics. Should you require further assistance or require any reasonable adjustments be put in place to better support your application process, please do not hesitate to raise this with us.
22/05/2026
Full time
About Us: Solirius Reply, part of the Reply Group, delivers technical consultancy and application delivery to our clients in order to solve real world problems and allow our clients to respond to an ever changing technical landscape. We partner closely with our clients, embedding our consultants into their businesses in order to provide a bespoke service, allowing us to truly understand our clients' needs. It is this close collaboration with our clients that has enabled us to grow rapidly in recent years and will drive our ambitious future growth plans. We currently have over 300 consultants working with a variety of key clients from both the public and private sectors such as the Ministry of Justice, Department for Education, FCDOS, UEFA, International Olympic Committee and Mercedes Benz; with plans to increase our client base further in the near future. We operate as a flat organisation and believe in trusting and supporting our team to operate independently. We pride ourselves on being specialists at what we do, making the most of our consultants' expertise in their fields in order to provide a best in class service to our clients. All our consultants have the opportunity to work on a range of different projects, providing a broad range of knowledge on which to develop their careers and progress in the direction they choose. About You: You are a motivated and adaptable professional with a strong analytical mindset and a passion for using technology to solve real world problems. You enjoy working in collaborative, agile teams and take pride in delivering high quality solutions that make a tangible impact. With strong communication skills and a consultative approach, you're comfortable engaging with clients, understanding their needs, and translating them into effective outcomes. You understand and align with Solirius Reply Values The Role: We are seeking a highly skilled Java Engineer with AI expertise to design, develop, and deploy intelligent, scalable applications. You will work at the intersection of backend engineering and artificial intelligence, building systems that integrate machine learning models, data pipelines, and cloud native services. This role is ideal for someone passionate about clean architecture, performance optimization, and applying AI technologies to real world business challenges. Key Responsibilities Design, develop, and maintain high-performance Java based applications Integrate AI/ML models into production grade backend systems Build RESTful APIs and microservices using modern Java frameworks Collaborate with data scientists to deploy and scale machine learning solutions Optimise system performance, scalability, and security Implement CI/CD pipelines and ensure high code quality standards Work with cloud platforms to deploy AI powered services Contribute to architecture decisions and technical roadmaps Required Qualifications Strong experience with Java 12+, Spring Boot, and microservices architecture Experience integrating AI/ML solutions into backend systems Understanding of REST APIs, distributed systems, and database design Familiarity with SQL and NoSQL databases Experience with cloud platforms (e.g., Amazon Web Services, Google Cloud Platform, or Microsoft Azure) Knowledge of containerisation technologies like Docker and orchestration tools such as Kubernetes Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java based ML libraries) Strong problem solving and communication skills Preferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with MLOps practices and model lifecycle management Knowledge of event driven architectures (Kafka or similar) Experience with DevOps tooling and infrastructure as code Exposure to Generative AI and large language models What We Offer: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development training per year Enhanced Parental Leave Paid Fertility Leave (5 Days) Statutory & Contributory Pension EAP with Gym Membership Benefits Flexible Working Annual Away Days/Company Socials Equality & Diversity: Solirius Reply is an equal opportunities employer. We are committed to creating a work environment that supports, celebrates, encourages, and respects all individuals and in which all processes are based on merit, competence and business needs. We do not discriminate on the basis of race, religion, gender, sexuality, age, disability, ethnicity, marital status or any other protected characteristics. Should you require further assistance or require any reasonable adjustments be put in place to better support your application process, please do not hesitate to raise this with us.
About Scrumconnect Consulting Scrumconnect Consulting is a multi-award-winning digital consultancy, recognised for delivering impactful technology solutions across UK government departments. Our work has positively influenced the lives of over 40 million UK citizens. With a strong commitment to user-centred design and agile delivery, we continue to build innovative digital services that truly make a difference. Overview: We are seeking a seasoned Data Lead to define and deliver a comprehensive data strategy for large-scale, citizen-facing services used by millions. This role involves assessing current data capabilities, defining a future vision, and architecting a roadmap to achieve it while building and leading the team required to deliver. Key Responsibilities: Data Strategy & Governance Lead the end-to-end data strategy across services Assess current ( as-is ) and future ( to-be ) states of data platforms and pipelines Develop a short- to medium-term strategic roadmap aligned with broader organisational and government data strategies Define and implement policies, standards, and governance frameworks for secure and scalable data services Technical Leadership & Architecture Select and evolve data engineering tools, frameworks, and methodologies Ensure alignment with enterprise architecture and technical strategies Lead delivery of complex data engineering initiatives across multiple systems Design solutions balancing functional and non-functional requirements Team Design & Delivery Define optimal team structure, including roles, skills, and capacity Build and lead multidisciplinary data teams (engineers, analysts, data scientists) Mentor and guide team members to ensure high-quality delivery Oversee implementation of data platforms, pipelines, and analytical models Standards, Compliance & Quality Ensure adherence to data governance, security, and compliance standards Embed data quality, lineage, and protection practices across systems Contribute to enterprise-wide data policies and regulatory compliance Required Experience & Skills: 10+ years of experience in data engineering, data science, or analytics Proven experience defining and executing data strategies in complex organisations Strong expertise in cloud-based data platforms (AWS preferred) Experience with modern ETL/ELT tools and data pipeline frameworks Solid understanding of data modelling, warehousing, and transformation best practices Experience across the data science/ML life cycle from prototype to production Experience working in public sector or regulated environments, with knowledge of GDPR and related standards Strong communication and stakeholder management skills, including engaging senior stakeholders Proven leadership, mentoring, and team-building capabilities Tech Stack: Google Analytics Google BigQuery Looker Studio Google Tag Manager Desirable Experience: Experience in public sector or citizen services (eg, benefits systems) Exposure to government frameworks or large-scale transformation programmes Security clearance (BPSS, SC, or DV) or willingness to obtain Diversity & Inclusion At Scrumconnect Consulting, we believe that diversity drives innovation. We are committed to creating an inclusive environment where every individual is respected, valued, and supported. We welcome applications from candidates of all backgrounds and experiences, and we actively encourage applications from women, people with disabilities, underrepresented communities, and those seeking flexible working arrangements.
22/05/2026
Full time
About Scrumconnect Consulting Scrumconnect Consulting is a multi-award-winning digital consultancy, recognised for delivering impactful technology solutions across UK government departments. Our work has positively influenced the lives of over 40 million UK citizens. With a strong commitment to user-centred design and agile delivery, we continue to build innovative digital services that truly make a difference. Overview: We are seeking a seasoned Data Lead to define and deliver a comprehensive data strategy for large-scale, citizen-facing services used by millions. This role involves assessing current data capabilities, defining a future vision, and architecting a roadmap to achieve it while building and leading the team required to deliver. Key Responsibilities: Data Strategy & Governance Lead the end-to-end data strategy across services Assess current ( as-is ) and future ( to-be ) states of data platforms and pipelines Develop a short- to medium-term strategic roadmap aligned with broader organisational and government data strategies Define and implement policies, standards, and governance frameworks for secure and scalable data services Technical Leadership & Architecture Select and evolve data engineering tools, frameworks, and methodologies Ensure alignment with enterprise architecture and technical strategies Lead delivery of complex data engineering initiatives across multiple systems Design solutions balancing functional and non-functional requirements Team Design & Delivery Define optimal team structure, including roles, skills, and capacity Build and lead multidisciplinary data teams (engineers, analysts, data scientists) Mentor and guide team members to ensure high-quality delivery Oversee implementation of data platforms, pipelines, and analytical models Standards, Compliance & Quality Ensure adherence to data governance, security, and compliance standards Embed data quality, lineage, and protection practices across systems Contribute to enterprise-wide data policies and regulatory compliance Required Experience & Skills: 10+ years of experience in data engineering, data science, or analytics Proven experience defining and executing data strategies in complex organisations Strong expertise in cloud-based data platforms (AWS preferred) Experience with modern ETL/ELT tools and data pipeline frameworks Solid understanding of data modelling, warehousing, and transformation best practices Experience across the data science/ML life cycle from prototype to production Experience working in public sector or regulated environments, with knowledge of GDPR and related standards Strong communication and stakeholder management skills, including engaging senior stakeholders Proven leadership, mentoring, and team-building capabilities Tech Stack: Google Analytics Google BigQuery Looker Studio Google Tag Manager Desirable Experience: Experience in public sector or citizen services (eg, benefits systems) Exposure to government frameworks or large-scale transformation programmes Security clearance (BPSS, SC, or DV) or willingness to obtain Diversity & Inclusion At Scrumconnect Consulting, we believe that diversity drives innovation. We are committed to creating an inclusive environment where every individual is respected, valued, and supported. We welcome applications from candidates of all backgrounds and experiences, and we actively encourage applications from women, people with disabilities, underrepresented communities, and those seeking flexible working arrangements.
AI Engineers & Technical AI Leaders London Hybrid We're supporting a major consulting and technology organisation delivering AI and data transformation programmes across Financial Services and Banking. The focus is applied AI engineering, building production grade AI solutions across banking, risk, fraud, automation and enterprise platforms. Hiring across multiple levels, from Engineers through to senior technical leadership. What you'll be doing Building AI-enabled platforms and intelligent workflows Working with LLMs, RAG pipelines and embedding models Developing scalable backend services and AI integrations Collaborating across engineering, architecture and business teams Supporting AI deployment, governance and operational rollout Environment Python, SQL LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases, FastAPI, APIs AWS, Azure, GCP or Databricks CI/CD, MLOps and LLMOps Requirements Strong software or data engineering foundations Experience delivering AI or AI enabled solutions Exposure to cloud and modern data platforms Financial Services or regulated industry experience essential Strong communication and stakeholder skills Open to candidates from Engineer through to Senior Manager level.
22/05/2026
Full time
AI Engineers & Technical AI Leaders London Hybrid We're supporting a major consulting and technology organisation delivering AI and data transformation programmes across Financial Services and Banking. The focus is applied AI engineering, building production grade AI solutions across banking, risk, fraud, automation and enterprise platforms. Hiring across multiple levels, from Engineers through to senior technical leadership. What you'll be doing Building AI-enabled platforms and intelligent workflows Working with LLMs, RAG pipelines and embedding models Developing scalable backend services and AI integrations Collaborating across engineering, architecture and business teams Supporting AI deployment, governance and operational rollout Environment Python, SQL LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases, FastAPI, APIs AWS, Azure, GCP or Databricks CI/CD, MLOps and LLMOps Requirements Strong software or data engineering foundations Experience delivering AI or AI enabled solutions Exposure to cloud and modern data platforms Financial Services or regulated industry experience essential Strong communication and stakeholder skills Open to candidates from Engineer through to Senior Manager level.
Qureight's mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market, faster. We're looking for talented people who want their work to matter. With offices in Cambridge and London, you'll join our multidisciplinary team of clinicians, scientists, and engineers. What unites us is our open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials. About the role As Qureight scales its AI-driven imaging platform and advances development of foundation models and disease-specific AI models, we are building the data engineering capability required to support large-scale data preparation for machine learning. We are looking for a Data Engineer to focus on preparing and managing large imaging datasets (including CT scans and DICOM metadata) for use in machine learning workflows. This role sits within the Science function and works closely with Machine Learning Scientists as well as other Data Engineers to ensure that data is delivered in a consistent, high-quality, and efficient format ready for model development. It will focus on designing and implementing the next iteration of our data infrastructure to accelerate our integration of machine learning into clinical trials. What you will do Collaborate on designing and implementing new data infrastructure and pipelines preparing data for large-scale ML workflows Care about data quality, and ensuring the pipelines you build are robust, scalable, and maintainable Work with DICOM data to feed into foundation model and disease-specific imaging model development Collaborate closely with Machine Learning Scientists, DevOps Engineers, and other Data Engineers to create a tight feedback loop and ensure the end-to-end process is effective and efficient Ensure that our data processes have quality and compliance designed in from the start to make reproducibility, lineage tracking, and data quality painless Scale pipelines to handle millions of scans - ingesting the imaging data, transforming it, filtering and structuring ready for foundation model development. What we need Proven experience as a Data Engineer in complex, data-rich environments Strong programming skills in Python Experience building and maintaining production ML data pipelines, including orchestration tools such as Dagster and cloud infrastructure on AWS Experience with Docker and Kubernetes based infrastructure, Experience working with large datasets Understanding of data preprocessing and quality control for machine learning Strong collaboration skills with machine learning or technical teams Even better if you have experience of Medical imaging data such as CT, MRI, or DICOM Large-scale datasets or foundation model workflows Deployment tooling (Helm and familiarity with Gitops tooling such as Flux and Kustomize) Data versioning and reproducibility frameworks Database design and data modelling Working in regulated or GxP or ISO 13485 environments Experience with ML experiment tracking or metadata management (MLFlow) Benefits A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, and a contributory pension scheme 25 days annual leave, plus bank holidays and enhanced maternity leave A diverse work environment that brings together experts in many fields, including software engineering, devops, data science, machine learning, quality assurance, regulatory affairs, and clinical operations. Everyone is welcome at Qureight. We are an equal opportunities employer and encourage applications from all suitably qualified candidates regardless of age, disability, ethnicity, sex, gender reassignment, religion or belief, sexual orientation, marriage and civil partnership, or pregnancy and maternity. Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply - you may be a great fit, even if you don't meet every qualification. We'd love to hear from you. If you require any adjustments to the application or selection process, please let us know. We will be happy to support you.
22/05/2026
Full time
Qureight's mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market, faster. We're looking for talented people who want their work to matter. With offices in Cambridge and London, you'll join our multidisciplinary team of clinicians, scientists, and engineers. What unites us is our open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials. About the role As Qureight scales its AI-driven imaging platform and advances development of foundation models and disease-specific AI models, we are building the data engineering capability required to support large-scale data preparation for machine learning. We are looking for a Data Engineer to focus on preparing and managing large imaging datasets (including CT scans and DICOM metadata) for use in machine learning workflows. This role sits within the Science function and works closely with Machine Learning Scientists as well as other Data Engineers to ensure that data is delivered in a consistent, high-quality, and efficient format ready for model development. It will focus on designing and implementing the next iteration of our data infrastructure to accelerate our integration of machine learning into clinical trials. What you will do Collaborate on designing and implementing new data infrastructure and pipelines preparing data for large-scale ML workflows Care about data quality, and ensuring the pipelines you build are robust, scalable, and maintainable Work with DICOM data to feed into foundation model and disease-specific imaging model development Collaborate closely with Machine Learning Scientists, DevOps Engineers, and other Data Engineers to create a tight feedback loop and ensure the end-to-end process is effective and efficient Ensure that our data processes have quality and compliance designed in from the start to make reproducibility, lineage tracking, and data quality painless Scale pipelines to handle millions of scans - ingesting the imaging data, transforming it, filtering and structuring ready for foundation model development. What we need Proven experience as a Data Engineer in complex, data-rich environments Strong programming skills in Python Experience building and maintaining production ML data pipelines, including orchestration tools such as Dagster and cloud infrastructure on AWS Experience with Docker and Kubernetes based infrastructure, Experience working with large datasets Understanding of data preprocessing and quality control for machine learning Strong collaboration skills with machine learning or technical teams Even better if you have experience of Medical imaging data such as CT, MRI, or DICOM Large-scale datasets or foundation model workflows Deployment tooling (Helm and familiarity with Gitops tooling such as Flux and Kustomize) Data versioning and reproducibility frameworks Database design and data modelling Working in regulated or GxP or ISO 13485 environments Experience with ML experiment tracking or metadata management (MLFlow) Benefits A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, and a contributory pension scheme 25 days annual leave, plus bank holidays and enhanced maternity leave A diverse work environment that brings together experts in many fields, including software engineering, devops, data science, machine learning, quality assurance, regulatory affairs, and clinical operations. Everyone is welcome at Qureight. We are an equal opportunities employer and encourage applications from all suitably qualified candidates regardless of age, disability, ethnicity, sex, gender reassignment, religion or belief, sexual orientation, marriage and civil partnership, or pregnancy and maternity. Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply - you may be a great fit, even if you don't meet every qualification. We'd love to hear from you. If you require any adjustments to the application or selection process, please let us know. We will be happy to support you.
Qureight's mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market, faster. We're looking for talented people who want their work to matter. With offices in Cambridge and London, you'll join our multidisciplinary team of clinicians, scientists, and engineers. What unites us is our open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials. About the role As Qureight scales its AI-driven imaging platform and advances development of foundation models and disease-specific AI models, we are building the data engineering capability required to support large-scale data preparation for machine learning. We are looking for a Data Engineer to focus on preparing and managing large imaging datasets (including CT scans and DICOM metadata) for use in machine learning workflows. This role sits within the Science function and works closely with Machine Learning Scientists as well as other Data Engineers to ensure that data is delivered in a consistent, high-quality, and efficient format ready for model development. It will focus on designing and implementing the next iteration of our data infrastructure to accelerate our integration of machine learning into clinical trials. What you will do Collaborate on designing and implementing new data infrastructure and pipelines preparing data for large-scale ML workflows Care about data quality, and ensuring the pipelines you build are robust, scalable, and maintainable Work with DICOM data to feed into foundation model and disease-specific imaging model development Collaborate closely with Machine Learning Scientists, DevOps Engineers, and other Data Engineers to create a tight feedback loop and ensure the end-to-end process is effective and efficient Ensure that our data processes have quality and compliance designed in from the start to make reproducibility, lineage tracking, and data quality painless Scale pipelines to handle millions of scans - ingesting the imaging data, transforming it, filtering and structuring ready for foundation model development. What we need Proven experience as a Data Engineer in complex, data-rich environments Strong programming skills in Python Experience building and maintaining production ML data pipelines, including orchestration tools such as Dagster and cloud infrastructure on AWS Experience with Docker and Kubernetes based infrastructure, Experience working with large datasets Understanding of data preprocessing and quality control for machine learning Strong collaboration skills with machine learning or technical teams Even better if you have experience of Medical imaging data such as CT, MRI, or DICOM Large-scale datasets or foundation model workflows Deployment tooling (Helm and familiarity with Gitops tooling such as Flux and Kustomize) Data versioning and reproducibility frameworks Database design and data modelling Working in regulated or GxP or ISO 13485 environments Experience with ML experiment tracking or metadata management (MLFlow) Benefits A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, and a contributory pension scheme 25 days annual leave, plus bank holidays and enhanced maternity leave A diverse work environment that brings together experts in many fields, including software engineering, devops, data science, machine learning, quality assurance, regulatory affairs, and clinical operations. Everyone is welcome at Qureight. We are an equal opportunities employer and encourage applications from all suitably qualified candidates regardless of age, disability, ethnicity, sex, gender reassignment, religion or belief, sexual orientation, marriage and civil partnership, or pregnancy and maternity. Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply - you may be a great fit, even if you don't meet every qualification. We'd love to hear from you. If you require any adjustments to the application or selection process, please let us know. We will be happy to support you.
22/05/2026
Full time
Qureight's mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market, faster. We're looking for talented people who want their work to matter. With offices in Cambridge and London, you'll join our multidisciplinary team of clinicians, scientists, and engineers. What unites us is our open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials. About the role As Qureight scales its AI-driven imaging platform and advances development of foundation models and disease-specific AI models, we are building the data engineering capability required to support large-scale data preparation for machine learning. We are looking for a Data Engineer to focus on preparing and managing large imaging datasets (including CT scans and DICOM metadata) for use in machine learning workflows. This role sits within the Science function and works closely with Machine Learning Scientists as well as other Data Engineers to ensure that data is delivered in a consistent, high-quality, and efficient format ready for model development. It will focus on designing and implementing the next iteration of our data infrastructure to accelerate our integration of machine learning into clinical trials. What you will do Collaborate on designing and implementing new data infrastructure and pipelines preparing data for large-scale ML workflows Care about data quality, and ensuring the pipelines you build are robust, scalable, and maintainable Work with DICOM data to feed into foundation model and disease-specific imaging model development Collaborate closely with Machine Learning Scientists, DevOps Engineers, and other Data Engineers to create a tight feedback loop and ensure the end-to-end process is effective and efficient Ensure that our data processes have quality and compliance designed in from the start to make reproducibility, lineage tracking, and data quality painless Scale pipelines to handle millions of scans - ingesting the imaging data, transforming it, filtering and structuring ready for foundation model development. What we need Proven experience as a Data Engineer in complex, data-rich environments Strong programming skills in Python Experience building and maintaining production ML data pipelines, including orchestration tools such as Dagster and cloud infrastructure on AWS Experience with Docker and Kubernetes based infrastructure, Experience working with large datasets Understanding of data preprocessing and quality control for machine learning Strong collaboration skills with machine learning or technical teams Even better if you have experience of Medical imaging data such as CT, MRI, or DICOM Large-scale datasets or foundation model workflows Deployment tooling (Helm and familiarity with Gitops tooling such as Flux and Kustomize) Data versioning and reproducibility frameworks Database design and data modelling Working in regulated or GxP or ISO 13485 environments Experience with ML experiment tracking or metadata management (MLFlow) Benefits A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, and a contributory pension scheme 25 days annual leave, plus bank holidays and enhanced maternity leave A diverse work environment that brings together experts in many fields, including software engineering, devops, data science, machine learning, quality assurance, regulatory affairs, and clinical operations. Everyone is welcome at Qureight. We are an equal opportunities employer and encourage applications from all suitably qualified candidates regardless of age, disability, ethnicity, sex, gender reassignment, religion or belief, sexual orientation, marriage and civil partnership, or pregnancy and maternity. Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply - you may be a great fit, even if you don't meet every qualification. We'd love to hear from you. If you require any adjustments to the application or selection process, please let us know. We will be happy to support you.
hackajob is collaborating with Accenture to connect them with exceptional professionals for this role. Role: Data & ML Engineer Location: Newcastle Upon Tyne Levels: Senior Analyst, Specialist Experience Level: 3+ years Please Note: Due to the nature of client work you will be undertaking, you will need to be willing to go through a Security Clearance (Including BPSS) process as part of this role, which requires 5+ years UK address history at the point of application. Hybrid Working: This role will require you to work from our Newcastle, Cobalt Business Park office for a minimum of 3 days per week. Role Overview As a Data & ML Engineer, you will design, build, and optimize scalable data pipelines and machine learning solutions. You'll work with client teams to deliver intelligent data products, leveraging modern cloud and AI technologies. Key Responsibilities Design and implement robust data pipelines and ML workflows using Python, SQL, Spark, and Databricks. Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments. Integrate data from diverse sources, including streaming and batch ingestion, using Azure Data Factory, GCP Dataflow and AWS services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform. Visualize and communicate insights using Power BI, Tableau, and PowerApps. Mentor junior engineers and contribute to internal knowledge sharing. Ensure solutions meet security, compliance, and performance standards. Qualifications Core Data & AI Skills Python, SQL, Spark, Scala Machine Learning, NLP, Deep Learning, Prompt engineering, Agentic AI Data Architecture, Data Modelling, Data Engineering, Data Analysis DevOps & Engineering CI/CD and MLOps (Azure DevOps, GitHub actions, Jenkins, Kubeflow etc) Infrastructure as Code (Terraform, Ansible etc) Containers (Kubernetes, Docker etc) Certifications & Tools Data Visualisation and UI (Power BI, PowerApps, Tableau etc) Data Science Platforms (Databricks, Snowflake etc) Cloud certifications (Azure, AWS, GCP) Cloud Native Data Engineering (Azure Data Factory, AWS Glue, GCP Dataflow etc) Other Requirements At least 3 years experience with large-scale data challenges (big data, distributed systems) Hands on with Infrastructure as Code (Terraform, Ansible) Agile and Waterfall project experience Strong stakeholder management and communication skills Security and compliance awareness Desirable Experience in client facing roles Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer) Experience mentoring or managing teams What's In It For You Competitive basic salary 25 days vacation per year Private medical insurance 3 extra days leave per year for charitable work of your choice Flexibility and mobility required to deliver this role; possible onsite client engagement
22/05/2026
Full time
hackajob is collaborating with Accenture to connect them with exceptional professionals for this role. Role: Data & ML Engineer Location: Newcastle Upon Tyne Levels: Senior Analyst, Specialist Experience Level: 3+ years Please Note: Due to the nature of client work you will be undertaking, you will need to be willing to go through a Security Clearance (Including BPSS) process as part of this role, which requires 5+ years UK address history at the point of application. Hybrid Working: This role will require you to work from our Newcastle, Cobalt Business Park office for a minimum of 3 days per week. Role Overview As a Data & ML Engineer, you will design, build, and optimize scalable data pipelines and machine learning solutions. You'll work with client teams to deliver intelligent data products, leveraging modern cloud and AI technologies. Key Responsibilities Design and implement robust data pipelines and ML workflows using Python, SQL, Spark, and Databricks. Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments. Integrate data from diverse sources, including streaming and batch ingestion, using Azure Data Factory, GCP Dataflow and AWS services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform. Visualize and communicate insights using Power BI, Tableau, and PowerApps. Mentor junior engineers and contribute to internal knowledge sharing. Ensure solutions meet security, compliance, and performance standards. Qualifications Core Data & AI Skills Python, SQL, Spark, Scala Machine Learning, NLP, Deep Learning, Prompt engineering, Agentic AI Data Architecture, Data Modelling, Data Engineering, Data Analysis DevOps & Engineering CI/CD and MLOps (Azure DevOps, GitHub actions, Jenkins, Kubeflow etc) Infrastructure as Code (Terraform, Ansible etc) Containers (Kubernetes, Docker etc) Certifications & Tools Data Visualisation and UI (Power BI, PowerApps, Tableau etc) Data Science Platforms (Databricks, Snowflake etc) Cloud certifications (Azure, AWS, GCP) Cloud Native Data Engineering (Azure Data Factory, AWS Glue, GCP Dataflow etc) Other Requirements At least 3 years experience with large-scale data challenges (big data, distributed systems) Hands on with Infrastructure as Code (Terraform, Ansible) Agile and Waterfall project experience Strong stakeholder management and communication skills Security and compliance awareness Desirable Experience in client facing roles Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer) Experience mentoring or managing teams What's In It For You Competitive basic salary 25 days vacation per year Private medical insurance 3 extra days leave per year for charitable work of your choice Flexibility and mobility required to deliver this role; possible onsite client engagement
hackajob is collaborating with Sage to connect them with exceptional professionals for this role. Sage is a forward thinking technology company that specialises in software. The team you'd be applying for models itself on creating a robust culture of belonging. We pride ourselves on fostering a fast paced, innovative environment where experimentation and continuous improvement are highly valued. Our infrastructure is built on AWS, enabling us to deliver robust and scalable solutions to our clients. The key purpose of this role is to help the team develop Embeddable UI components using React as the preferred technology of choice. You will be supported by being positioned in a squad with a strong lead, principal, senior, mid level and graduate engineer set up, that will support your growth as well as a leader who will invest in your career. This is a hybrid role, requiring three days per week in our Newcastle office. In This Role You'll Design, develop, and maintain a new high quality, scalable front end application that integrates with internal APIs bringing it together as a complete solution. You will collaborate closely with Product, Design, and QA to ship an elegant, performant, and reliable product that delivers a seamless user experience. In Addition, You Will Join a Team That Also Design, develop, and maintain scalable and high performance APIs and backend services using C#, .NET and node.js technologies that integrate with other Sage products. Collaborate with global teams across Sage, to define, design, deliver and maintain services across the Payroll and HR Business Unit. Work cross functionally with various Sage teams: Product management, QA/XD, various product lines and business units to deliver for our customers. Ensure the performance, quality, and responsiveness of applications. Resolve defects/bugs during QA testing, pre production, production, and post release patches.Help maintain code quality, organization, and automatization. Utilize AWS services to build, deploy, and manage applications. Experiment with new technologies and methodologies to improve our development processes and product offerings. Participate in code reviews, providing constructive feedback to peers. Maintain relevant documentation to describe logic, coding/configuration, testing and changes where applicable. Contribute to the continuous improvement of our software development lifecycle. Be an active and enthusiastic team player. Partner effectively with all team members to deliver against commitments. What We're Looking For Experience in front end development with a focus on React/Accessibility etc Experience in software development with a focus on C#, .NET and/or node.js. Experience using Github Co-Pilot as a complimentary tool building on your own skills making deliver as efficient as possible. Experienced in building and consuming APIs and backend services. Knowledge of AWS services (e.g., EC2, S3, RDS, Lambda, API Gateway, DocumentDB etc.) Proven experience with Agile Development & SCRUM Experience with relational databases would be beneficial (e.g., SQL Server, MySQL) and/or NoSQL databases (e.g., DynamoDB, MongoDB). Experience with version control in Git and CI/CD pipelines. Strong problem solving skills and attention to detail. Ability to work effectively in a fast paced, agile environment. Good communication and collaboration skills. Bachelor's degree in computer science, Engineering, or a related field, or equivalent work experience.
22/05/2026
Full time
hackajob is collaborating with Sage to connect them with exceptional professionals for this role. Sage is a forward thinking technology company that specialises in software. The team you'd be applying for models itself on creating a robust culture of belonging. We pride ourselves on fostering a fast paced, innovative environment where experimentation and continuous improvement are highly valued. Our infrastructure is built on AWS, enabling us to deliver robust and scalable solutions to our clients. The key purpose of this role is to help the team develop Embeddable UI components using React as the preferred technology of choice. You will be supported by being positioned in a squad with a strong lead, principal, senior, mid level and graduate engineer set up, that will support your growth as well as a leader who will invest in your career. This is a hybrid role, requiring three days per week in our Newcastle office. In This Role You'll Design, develop, and maintain a new high quality, scalable front end application that integrates with internal APIs bringing it together as a complete solution. You will collaborate closely with Product, Design, and QA to ship an elegant, performant, and reliable product that delivers a seamless user experience. In Addition, You Will Join a Team That Also Design, develop, and maintain scalable and high performance APIs and backend services using C#, .NET and node.js technologies that integrate with other Sage products. Collaborate with global teams across Sage, to define, design, deliver and maintain services across the Payroll and HR Business Unit. Work cross functionally with various Sage teams: Product management, QA/XD, various product lines and business units to deliver for our customers. Ensure the performance, quality, and responsiveness of applications. Resolve defects/bugs during QA testing, pre production, production, and post release patches.Help maintain code quality, organization, and automatization. Utilize AWS services to build, deploy, and manage applications. Experiment with new technologies and methodologies to improve our development processes and product offerings. Participate in code reviews, providing constructive feedback to peers. Maintain relevant documentation to describe logic, coding/configuration, testing and changes where applicable. Contribute to the continuous improvement of our software development lifecycle. Be an active and enthusiastic team player. Partner effectively with all team members to deliver against commitments. What We're Looking For Experience in front end development with a focus on React/Accessibility etc Experience in software development with a focus on C#, .NET and/or node.js. Experience using Github Co-Pilot as a complimentary tool building on your own skills making deliver as efficient as possible. Experienced in building and consuming APIs and backend services. Knowledge of AWS services (e.g., EC2, S3, RDS, Lambda, API Gateway, DocumentDB etc.) Proven experience with Agile Development & SCRUM Experience with relational databases would be beneficial (e.g., SQL Server, MySQL) and/or NoSQL databases (e.g., DynamoDB, MongoDB). Experience with version control in Git and CI/CD pipelines. Strong problem solving skills and attention to detail. Ability to work effectively in a fast paced, agile environment. Good communication and collaboration skills. Bachelor's degree in computer science, Engineering, or a related field, or equivalent work experience.
What we do: Zero100 is a membership-based intelligence company that connects, informs, and inspires the world's most influential C-Level Operations & Supply Chain Officers - and their teams - to unlock the true potential of the AI and Digital Revolution. Our members use Zero100's research, advisory services, data, and peer community, to sharpen strategy, challenge assumptions, and accelerate progress on their most important transformation priorities from AI adoption and digitization to resilience and decarbonization. With a rapidly expanding headquarters in central London, Zero100's members include Nike, Walmart, Unilever, Pfizer, Google, Honeywell, and General Motors. Recent recognition: 2026 King's Award for Enterprise in the International Trade The Sunday Times Best Places to Work 2025 The Sunday Times 100 (), 2025 LinkedIn Top 25 Start-Ups (), 2025 What you will do: Note that this is a primarily office-based role ( 4 days per week). As a Senior AI Engineer at Zero100, you will play a central role in building and scaling the AI/ML and agentic systems that power our research, product, and member-facing teams. You'll be hands-on across the full stack: designing and operating data pipelines, building production-grade intelligent systems, and prototyping new approaches to enhance our capabilities. This is an end-to-end role where you'll own projects from ideation to production, working collaboratively with a senior engineering lead while having the autonomy to drive work forward independently. You'll partner closely with colleagues in research, product, membership, and revenue operations, thriving in an environment where you can balance engineering rigour with experimentation and help shape our technical foundations as we scale. Responsibilities: Design and build production-grade AI/ML and agentic systems, including agent orchestration, tool integration, and retrieval-augmented generation Develop and operate scalable, reliable data pipelines that serve both AI/ML systems and broader research and analytical needs across the organisation Collaborate with a senior engineering lead to architect and iterate on system designs, while taking ownership of implementation and delivery Build and maintain robust infrastructure with a focus on deployment, monitoring, and long-term maintainability Conduct exploratory prototyping of new AI/ML approaches to inform product direction and system design Work closely with research, product, and member-facing teams to understand data requirements and deliver clean, reusable data products Champion best practices around data architecture, governance (e.g., Unity Catalog), and performance tuning Contribute to engineering standards, documentation, and processes as the team scales Qualifications: 5 years of experience in data and ML engineering roles, ideally in startup or high-growth environments, with a track record of owning end-to-end projects Experience building production-grade data pipelines and AI/ML systems (primarily in Python and SQL) in cloud environments, with an emphasis on scalability, code clarity, and long-term maintainability Hands on experience with Databricks, Spark, especially Delta Lake, Unity Catalog, Mlflow. Experience working with Knowledge Graphs and building Graph Databases. Deep familiarity with cloud platforms, particularly AWS and Google Cloud Experience deploying and monitoring ML models in production, including CI/CD practices, containerization, and API development Ability to deploy Opensource LLMs on local hardware or cloud platforms Strong software engineering fundamentals: version control, testing, code review, and documentation A genuine interest in agentic AI systems and emerging LLM-based architectures and frameworks such as Langchain/Langgraph/Deepagents. Proven ability to manage production infrastructure and data architecture in a fast paced environment Strong communication skills and ability to work with stakeholders to understand needs and explain complex ideas clearly Comfortable with ambiguity and excited to help shape processes, standards, and infrastructure as we scale Benefits: Competitive salary and bonus scheme Unlimited holidays Private healthcare & Life Insurance Enhanced pension Enhanced Parental Leave Policy Custom designed offices in central London with free breakfasts & snacks Zero100 is an Equal Opportunity-Affirmative Action Employer, welcoming applications from individuals of all backgrounds. We embrace diversity and inclusion in our workplace.
22/05/2026
Full time
What we do: Zero100 is a membership-based intelligence company that connects, informs, and inspires the world's most influential C-Level Operations & Supply Chain Officers - and their teams - to unlock the true potential of the AI and Digital Revolution. Our members use Zero100's research, advisory services, data, and peer community, to sharpen strategy, challenge assumptions, and accelerate progress on their most important transformation priorities from AI adoption and digitization to resilience and decarbonization. With a rapidly expanding headquarters in central London, Zero100's members include Nike, Walmart, Unilever, Pfizer, Google, Honeywell, and General Motors. Recent recognition: 2026 King's Award for Enterprise in the International Trade The Sunday Times Best Places to Work 2025 The Sunday Times 100 (), 2025 LinkedIn Top 25 Start-Ups (), 2025 What you will do: Note that this is a primarily office-based role ( 4 days per week). As a Senior AI Engineer at Zero100, you will play a central role in building and scaling the AI/ML and agentic systems that power our research, product, and member-facing teams. You'll be hands-on across the full stack: designing and operating data pipelines, building production-grade intelligent systems, and prototyping new approaches to enhance our capabilities. This is an end-to-end role where you'll own projects from ideation to production, working collaboratively with a senior engineering lead while having the autonomy to drive work forward independently. You'll partner closely with colleagues in research, product, membership, and revenue operations, thriving in an environment where you can balance engineering rigour with experimentation and help shape our technical foundations as we scale. Responsibilities: Design and build production-grade AI/ML and agentic systems, including agent orchestration, tool integration, and retrieval-augmented generation Develop and operate scalable, reliable data pipelines that serve both AI/ML systems and broader research and analytical needs across the organisation Collaborate with a senior engineering lead to architect and iterate on system designs, while taking ownership of implementation and delivery Build and maintain robust infrastructure with a focus on deployment, monitoring, and long-term maintainability Conduct exploratory prototyping of new AI/ML approaches to inform product direction and system design Work closely with research, product, and member-facing teams to understand data requirements and deliver clean, reusable data products Champion best practices around data architecture, governance (e.g., Unity Catalog), and performance tuning Contribute to engineering standards, documentation, and processes as the team scales Qualifications: 5 years of experience in data and ML engineering roles, ideally in startup or high-growth environments, with a track record of owning end-to-end projects Experience building production-grade data pipelines and AI/ML systems (primarily in Python and SQL) in cloud environments, with an emphasis on scalability, code clarity, and long-term maintainability Hands on experience with Databricks, Spark, especially Delta Lake, Unity Catalog, Mlflow. Experience working with Knowledge Graphs and building Graph Databases. Deep familiarity with cloud platforms, particularly AWS and Google Cloud Experience deploying and monitoring ML models in production, including CI/CD practices, containerization, and API development Ability to deploy Opensource LLMs on local hardware or cloud platforms Strong software engineering fundamentals: version control, testing, code review, and documentation A genuine interest in agentic AI systems and emerging LLM-based architectures and frameworks such as Langchain/Langgraph/Deepagents. Proven ability to manage production infrastructure and data architecture in a fast paced environment Strong communication skills and ability to work with stakeholders to understand needs and explain complex ideas clearly Comfortable with ambiguity and excited to help shape processes, standards, and infrastructure as we scale Benefits: Competitive salary and bonus scheme Unlimited holidays Private healthcare & Life Insurance Enhanced pension Enhanced Parental Leave Policy Custom designed offices in central London with free breakfasts & snacks Zero100 is an Equal Opportunity-Affirmative Action Employer, welcoming applications from individuals of all backgrounds. We embrace diversity and inclusion in our workplace.
You will need to login before you can apply for a job. Site Name: London The Stanley Building, Heidelberg, Switzerland - Zug, USA - Massachusetts - Cambridge Posted Date: Apr At GSK, we are actively working on building a future in which state-of-the-art software, Artificial Intelligence (AI) and Machine Learning (ML) enable us to develop new therapies and personalized medicines that drive better outcomes for patients at reduced cost with fewer side effects. This ambitious mission requires scalable, cloud-native solutions at the forefront of Software Engineering, Cloud Infrastructure, Efficient Compute, Machine Learning and AI. If this excites you, we would love to chat. About the Role To strengthen our AI for Science (AI4S) team, we are looking for Software Engineers with a track record in developing production-grade, data-driven software solutions. You will drive the development of scalable cloud infrastructure and efficient compute solutions to support large-scale AI models and agentic systems - building robust, high-performance software that enables scientific research using modern cloud technologies and the vast biomedical data sources available at GSK. Team Culture The AI4S team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we are motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. We strongly encourage applications from people with diverse and underrepresented backgrounds and perspectives. In this role you will Design and implement scalable infrastructure and software solutions to support large-scale AI models and agentic systems across the entire software development life cycle. Design and implement sophisticated machine learning and deep learning pipelines that can handle massive amounts of data with optimal resource utilization. Develop and maintain cloud-native architectures that enable seamless deployment and scaling of AI/ML workloads. Deliver robust, tested and high-performance code in an agile environment. Liaise with AI/ML engineers, data scientists, and domain experts to ensure fit-for-purpose infrastructure and data pipelines for cutting-edge scientific projects. Qualifications & Skills A degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering, among others); OR equivalent work experience as a professional software engineer. Demonstrated advanced programming expertise in Python and in developing and delivering robust, scalable software solutions. Experience with cloud platforms (AWS, GCP, Azure) and cloud-native architectures. Passion for software design and commitment to the development of reusable, scalable, and testable software components. Basic understanding of at least one major deep learning framework (PyTorch, JAX, TensorFlow). Knowledge of command-line tools and shell scripting. Knowledge of software engineering best practices, including continuous integration (CI) and continuous deployment (CD), containerization, and infrastructure as code. Strong problem-solving and debugging skills, and experience working in cluster settings or cloud-based environments. Fluency in English. Preferred Qualifications & Skills Familiarity with machine learning principles and state-of-the-art modelling approaches. Experience in design, development and deployment of commercial cloud-native software and infrastructure. Experience building and deploying large-scale AI models and agentic systems in production environments. Experience architecting, developing, and deploying distributed training pipelines for large models with PyTorch or TensorFlow. Expertise in performance optimization, cost optimization, and efficient compute resource management in cloud environments. Contributions to relevant open-source projects. Knowledge or interest in disease biology, molecular biology and medicine. Experience working with biomedical data (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images). Benefits The US salary ranges for new hires in this position range from $136,125 to $226,875 and include an annual bonus and eligibility to participate in a share-based long term incentive program. Benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. Why GSK? GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We are committed to creating an environment where our people can thrive and focus on what matters most. Equal Opportunity Employer GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
22/05/2026
Full time
You will need to login before you can apply for a job. Site Name: London The Stanley Building, Heidelberg, Switzerland - Zug, USA - Massachusetts - Cambridge Posted Date: Apr At GSK, we are actively working on building a future in which state-of-the-art software, Artificial Intelligence (AI) and Machine Learning (ML) enable us to develop new therapies and personalized medicines that drive better outcomes for patients at reduced cost with fewer side effects. This ambitious mission requires scalable, cloud-native solutions at the forefront of Software Engineering, Cloud Infrastructure, Efficient Compute, Machine Learning and AI. If this excites you, we would love to chat. About the Role To strengthen our AI for Science (AI4S) team, we are looking for Software Engineers with a track record in developing production-grade, data-driven software solutions. You will drive the development of scalable cloud infrastructure and efficient compute solutions to support large-scale AI models and agentic systems - building robust, high-performance software that enables scientific research using modern cloud technologies and the vast biomedical data sources available at GSK. Team Culture The AI4S team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we are motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. We strongly encourage applications from people with diverse and underrepresented backgrounds and perspectives. In this role you will Design and implement scalable infrastructure and software solutions to support large-scale AI models and agentic systems across the entire software development life cycle. Design and implement sophisticated machine learning and deep learning pipelines that can handle massive amounts of data with optimal resource utilization. Develop and maintain cloud-native architectures that enable seamless deployment and scaling of AI/ML workloads. Deliver robust, tested and high-performance code in an agile environment. Liaise with AI/ML engineers, data scientists, and domain experts to ensure fit-for-purpose infrastructure and data pipelines for cutting-edge scientific projects. Qualifications & Skills A degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering, among others); OR equivalent work experience as a professional software engineer. Demonstrated advanced programming expertise in Python and in developing and delivering robust, scalable software solutions. Experience with cloud platforms (AWS, GCP, Azure) and cloud-native architectures. Passion for software design and commitment to the development of reusable, scalable, and testable software components. Basic understanding of at least one major deep learning framework (PyTorch, JAX, TensorFlow). Knowledge of command-line tools and shell scripting. Knowledge of software engineering best practices, including continuous integration (CI) and continuous deployment (CD), containerization, and infrastructure as code. Strong problem-solving and debugging skills, and experience working in cluster settings or cloud-based environments. Fluency in English. Preferred Qualifications & Skills Familiarity with machine learning principles and state-of-the-art modelling approaches. Experience in design, development and deployment of commercial cloud-native software and infrastructure. Experience building and deploying large-scale AI models and agentic systems in production environments. Experience architecting, developing, and deploying distributed training pipelines for large models with PyTorch or TensorFlow. Expertise in performance optimization, cost optimization, and efficient compute resource management in cloud environments. Contributions to relevant open-source projects. Knowledge or interest in disease biology, molecular biology and medicine. Experience working with biomedical data (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images). Benefits The US salary ranges for new hires in this position range from $136,125 to $226,875 and include an annual bonus and eligibility to participate in a share-based long term incentive program. Benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. Why GSK? GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We are committed to creating an environment where our people can thrive and focus on what matters most. Equal Opportunity Employer GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
Ready to make travel easier for millions? Airalo is the world's first and largest eSIM store, helping travellers stay connected seamlessly in over 200 countries and regions. We trust our teams to take ownership, put customers first, and do work that has a real impact every day. What's in it for you? Airalo offers team members a range of perks, including remote work, generous PTO, wellness and learning allowances, and, of course, our annual Airalo Away retreat. Learn more about our benefits here; Hi, I'm Andra, Director of Data at Airalo! Our team works across the full data ecosystem, from collection to insights activation, ensuring that every piece of data drives meaningful action. We're curious problem-solvers who love tackling challenges that haven't been solved before and building tools and processes that scale impact across the company. Airalo's fully remote Data team is growing. You'll turn numbers into decisions that shape the future of our business, collaborating with cross-functional teams to solve complex problems and influence how millions of travellers stay connected. This isn't just dashboards - it's using data to drive strategy, inform product and growth decisions, and create real impact. You'll have access to best-in-class tools, the freedom to experiment, and a team ready to turn insights into action. As the Data Engineering Manager, you will lead the foundational backend of our data organization. You will directly manage our current pod of Data Engineers (2 Senior Data Engineers and 1 Customer Data Platform Engineer) and shape the hiring roadmap as the function grows - including scoping future specialized roles such as Machine Learning Engineers. Partnering closely with the Data Director, you will help us transition out of the reactive, ad-hoc phase and into a structured, highly scalable data ecosystem. You will own the architecture, ingestion, and orchestration that powers the rest of the data team - ensuring that our Analytics Engineers, Data Analysts and other users have a rock-solid, high-quality foundation to build upon. This role goes beyond building a data platform. You'll be the connective tissue between Product & Engineering, MarTech, and our partner ecosystem - ensuring data is produced cleanly at the source, captured reliably, and delivered cohesively across the entire organization. What You Will Do: Manage, mentor, and grow a high-performing team of Senior Data Engineers and CDP Engineers. Drive hiring for the Data Engineering function as it grows, including scoping future specialized roles such as Machine Learning Engineers. Foster a culture of engineering excellence, continuous learning, and cross-pollination of knowledge. Own the technical roadmap for Airalo's data infrastructure (GCP, BigQuery), orchestration (Dagster, Airflow), and ingestion (Fivetran, custom APIs). Drive data-platform architecture decisions, turning ambiguous business problems into scalable, production-grade technical designs. Bridge the data platform with MarTech and third party ecosystems (PSPs, MNOs, CDPs, attribution platforms), ensuring customer events, campaign data, and partner integrations flow cohesively in both directions. Partner with Software Engineering to embed data quality at the source - implementing data contracts, co owning schema decisions, and driving the rollout of a data catalogue across the organization. Establish the foundations for real time data capabilities as the business matures beyond batch processing. Design systems that prioritize data quality, privacy, and governance standards across all data initiatives. Transition the team's workflow from reactive problem solving to structured, agile delivery. Oversee the maintenance and optimization of high performance data pipelines, implementing CI/CD automation, observability frameworks, and strict data quality gates. Roll up your sleeves when necessary to assist with complex code reviews, Python/Scala development, or unblocking the team on difficult architectural challenges. Act as a strategic partner to the Analytics Engineering Manager and Data Director to build the backend requirements necessary to achieve our company wide goal of 80 % self serve analytics. Must-haves: 7+ years of professional experience as a Data/Software Engineer, with at least 2+ years of experience directly managing and scaling data engineering teams. You thrive in low maturity or greenfield data environments. You're comfortable navigating ambiguity and enjoy the process of laying down paved roads and engineering standards where none existed before. Deep, hands on background with major cloud platforms (GCP preferred) and cloud native data warehouses (BigQuery preferred, or Snowflake/Redshift). Strong experience with orchestration tools (Airflow, Dagster), ELT pipelines (Fivetran, dbt), and distributed data processing frameworks (Apache Spark, Flink). Hands on experience using AI tools to accelerate engineering workflows - code generation, code review, pipeline debugging, or documentation. Strong coding experience in Python (and/or Scala) and advanced SQL across relational and non relational databases. Experience implementing CI/CD, Infrastructure as Code, and observability/monitoring for data pipelines. Bachelor's degree in Computer Science, Engineering, Statistics, Information Systems, or a related quantitative field. Nice-to-have: Experience implementing data contracts, data catalogues (Atlan, Amundsen, DataHub), or federated governance models. Experience with Customer Data Platforms (Segment, mParticle, or similar), MarTech data integration, and real time event processing. Experience in marketplace, B2C, or high volume transactional businesses. Previous work in globally distributed data environments (multi currency, multi region, multi language). Experience building or contributing to experimentation platform infrastructure (A/B testing pipelines, feature flag data, experiment analysis frameworks). Exposure to Machine Learning infrastructure - not necessarily building models, but scoping teams, tooling, and pipelines that support ML workloads. If you are interested in this position, please apply via the link. Please note that to be considered for this role, you must reside in and be fully eligible to work in either Romania, Spain, or the UK. Proof of a valid right to work in one of these three countries will be required. By applying, you acknowledge and agree that, in case of successful application, Airalo may request to run background checks as a condition for entering into an agreement with you. Rest assured that these checks will only occur upon your prior consent and at the end of the selection process, and will be strictly limited to what is allowed under the laws that are applicable to you. All data that you share or that we collect in connection with such checks will be processed in accordance with our Privacy Policy, available here: We sincerely thank all applicants in advance for submitting their interest in this opportunity. Airalo is an equal opportunity employer and values diversity, equity & inclusion. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations upon request for individuals with disabilities throughout our job interview process.
21/05/2026
Full time
Ready to make travel easier for millions? Airalo is the world's first and largest eSIM store, helping travellers stay connected seamlessly in over 200 countries and regions. We trust our teams to take ownership, put customers first, and do work that has a real impact every day. What's in it for you? Airalo offers team members a range of perks, including remote work, generous PTO, wellness and learning allowances, and, of course, our annual Airalo Away retreat. Learn more about our benefits here; Hi, I'm Andra, Director of Data at Airalo! Our team works across the full data ecosystem, from collection to insights activation, ensuring that every piece of data drives meaningful action. We're curious problem-solvers who love tackling challenges that haven't been solved before and building tools and processes that scale impact across the company. Airalo's fully remote Data team is growing. You'll turn numbers into decisions that shape the future of our business, collaborating with cross-functional teams to solve complex problems and influence how millions of travellers stay connected. This isn't just dashboards - it's using data to drive strategy, inform product and growth decisions, and create real impact. You'll have access to best-in-class tools, the freedom to experiment, and a team ready to turn insights into action. As the Data Engineering Manager, you will lead the foundational backend of our data organization. You will directly manage our current pod of Data Engineers (2 Senior Data Engineers and 1 Customer Data Platform Engineer) and shape the hiring roadmap as the function grows - including scoping future specialized roles such as Machine Learning Engineers. Partnering closely with the Data Director, you will help us transition out of the reactive, ad-hoc phase and into a structured, highly scalable data ecosystem. You will own the architecture, ingestion, and orchestration that powers the rest of the data team - ensuring that our Analytics Engineers, Data Analysts and other users have a rock-solid, high-quality foundation to build upon. This role goes beyond building a data platform. You'll be the connective tissue between Product & Engineering, MarTech, and our partner ecosystem - ensuring data is produced cleanly at the source, captured reliably, and delivered cohesively across the entire organization. What You Will Do: Manage, mentor, and grow a high-performing team of Senior Data Engineers and CDP Engineers. Drive hiring for the Data Engineering function as it grows, including scoping future specialized roles such as Machine Learning Engineers. Foster a culture of engineering excellence, continuous learning, and cross-pollination of knowledge. Own the technical roadmap for Airalo's data infrastructure (GCP, BigQuery), orchestration (Dagster, Airflow), and ingestion (Fivetran, custom APIs). Drive data-platform architecture decisions, turning ambiguous business problems into scalable, production-grade technical designs. Bridge the data platform with MarTech and third party ecosystems (PSPs, MNOs, CDPs, attribution platforms), ensuring customer events, campaign data, and partner integrations flow cohesively in both directions. Partner with Software Engineering to embed data quality at the source - implementing data contracts, co owning schema decisions, and driving the rollout of a data catalogue across the organization. Establish the foundations for real time data capabilities as the business matures beyond batch processing. Design systems that prioritize data quality, privacy, and governance standards across all data initiatives. Transition the team's workflow from reactive problem solving to structured, agile delivery. Oversee the maintenance and optimization of high performance data pipelines, implementing CI/CD automation, observability frameworks, and strict data quality gates. Roll up your sleeves when necessary to assist with complex code reviews, Python/Scala development, or unblocking the team on difficult architectural challenges. Act as a strategic partner to the Analytics Engineering Manager and Data Director to build the backend requirements necessary to achieve our company wide goal of 80 % self serve analytics. Must-haves: 7+ years of professional experience as a Data/Software Engineer, with at least 2+ years of experience directly managing and scaling data engineering teams. You thrive in low maturity or greenfield data environments. You're comfortable navigating ambiguity and enjoy the process of laying down paved roads and engineering standards where none existed before. Deep, hands on background with major cloud platforms (GCP preferred) and cloud native data warehouses (BigQuery preferred, or Snowflake/Redshift). Strong experience with orchestration tools (Airflow, Dagster), ELT pipelines (Fivetran, dbt), and distributed data processing frameworks (Apache Spark, Flink). Hands on experience using AI tools to accelerate engineering workflows - code generation, code review, pipeline debugging, or documentation. Strong coding experience in Python (and/or Scala) and advanced SQL across relational and non relational databases. Experience implementing CI/CD, Infrastructure as Code, and observability/monitoring for data pipelines. Bachelor's degree in Computer Science, Engineering, Statistics, Information Systems, or a related quantitative field. Nice-to-have: Experience implementing data contracts, data catalogues (Atlan, Amundsen, DataHub), or federated governance models. Experience with Customer Data Platforms (Segment, mParticle, or similar), MarTech data integration, and real time event processing. Experience in marketplace, B2C, or high volume transactional businesses. Previous work in globally distributed data environments (multi currency, multi region, multi language). Experience building or contributing to experimentation platform infrastructure (A/B testing pipelines, feature flag data, experiment analysis frameworks). Exposure to Machine Learning infrastructure - not necessarily building models, but scoping teams, tooling, and pipelines that support ML workloads. If you are interested in this position, please apply via the link. Please note that to be considered for this role, you must reside in and be fully eligible to work in either Romania, Spain, or the UK. Proof of a valid right to work in one of these three countries will be required. By applying, you acknowledge and agree that, in case of successful application, Airalo may request to run background checks as a condition for entering into an agreement with you. Rest assured that these checks will only occur upon your prior consent and at the end of the selection process, and will be strictly limited to what is allowed under the laws that are applicable to you. All data that you share or that we collect in connection with such checks will be processed in accordance with our Privacy Policy, available here: We sincerely thank all applicants in advance for submitting their interest in this opportunity. Airalo is an equal opportunity employer and values diversity, equity & inclusion. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations upon request for individuals with disabilities throughout our job interview process.
Teamwork makes the stream work. Roku is changing how the world watches TV Roku is the TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers. From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. About the Team The mission of Roku's Data Engineering team is to develop a world-class big data platform that empowers both internal and external partners to leverage data and drive business growth. The team works closely with business stakeholders and engineering colleagues to collect, transform and surface metrics that are critical to the success of new and existing initiatives. As a Senior Data Engineer in the Viewer Product Device & Themed Experiences team, you'll play a pivotal role in designing data models and building scalable pipelines to capture business metrics across Roku devices, Roku Powered TVs, web, and mobile clients. This work is essential to helping Roku understand which features resonate most with users and how we can continue to improve their experience. About the Role With tens of millions of devices sold across multiple countries, thousands of streaming channels, and billions of hours watched, a scalable, reliable and fault-tolerant big data platform is critical to our continued success. This role is offered on a hybrid basis, based from our Cambridge Office, UK. What You'll Be Doing Building highly scalable, fault-tolerant distributed data processing systems (batch and streaming) that handle tens of terabytes of data each day, supporting a petabyte-scale data warehouse. Designing and developing robust data solutions, streamlining complex datasets into simplified, self-service models. Developing pipelines that ensure high data quality and resilience to imperfect source data. Defining and maintaining data mappings, business logic, transformations and data quality standards. Debugging low-level systems, measuring performance and optimising large production clusters. Taking part in architecture discussions, influencing the product roadmap, and owning new initiatives from concept to delivery. Maintaining and evolving existing platforms, introducing modern technologies and architectures where appropriate. We're Excited If You Have Strong SQL skills. Proficiency in at least one scripting language - Python is required. Proficiency in at least one object-oriented language. Experience with big data technologies such as HDFS, YARN, MapReduce, Hive, Kafka, Spark, Airflow, or Presto. Experience with AWS, GCP, or Looker (advantageous but not essential). Solid background in data modelling, including the design, implementation and optimisation of conceptual, logical, and physical models for scalable architectures. A degree in Computer Science (BS required; MS preferred). Our Hybrid Work Approach Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy. Benefits Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. Accommodations Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to .
21/05/2026
Full time
Teamwork makes the stream work. Roku is changing how the world watches TV Roku is the TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers. From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. About the Team The mission of Roku's Data Engineering team is to develop a world-class big data platform that empowers both internal and external partners to leverage data and drive business growth. The team works closely with business stakeholders and engineering colleagues to collect, transform and surface metrics that are critical to the success of new and existing initiatives. As a Senior Data Engineer in the Viewer Product Device & Themed Experiences team, you'll play a pivotal role in designing data models and building scalable pipelines to capture business metrics across Roku devices, Roku Powered TVs, web, and mobile clients. This work is essential to helping Roku understand which features resonate most with users and how we can continue to improve their experience. About the Role With tens of millions of devices sold across multiple countries, thousands of streaming channels, and billions of hours watched, a scalable, reliable and fault-tolerant big data platform is critical to our continued success. This role is offered on a hybrid basis, based from our Cambridge Office, UK. What You'll Be Doing Building highly scalable, fault-tolerant distributed data processing systems (batch and streaming) that handle tens of terabytes of data each day, supporting a petabyte-scale data warehouse. Designing and developing robust data solutions, streamlining complex datasets into simplified, self-service models. Developing pipelines that ensure high data quality and resilience to imperfect source data. Defining and maintaining data mappings, business logic, transformations and data quality standards. Debugging low-level systems, measuring performance and optimising large production clusters. Taking part in architecture discussions, influencing the product roadmap, and owning new initiatives from concept to delivery. Maintaining and evolving existing platforms, introducing modern technologies and architectures where appropriate. We're Excited If You Have Strong SQL skills. Proficiency in at least one scripting language - Python is required. Proficiency in at least one object-oriented language. Experience with big data technologies such as HDFS, YARN, MapReduce, Hive, Kafka, Spark, Airflow, or Presto. Experience with AWS, GCP, or Looker (advantageous but not essential). Solid background in data modelling, including the design, implementation and optimisation of conceptual, logical, and physical models for scalable architectures. A degree in Computer Science (BS required; MS preferred). Our Hybrid Work Approach Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy. Benefits Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. Accommodations Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to .
Client-facing R&D Generative AI Architect Trending Job Info Job Identification 11937 Posting Date 03/26/2026, 11:20 AM Job Role AI Engineer-AI Solutions Architect Experience (In Years) 6-9 Job Location London Job Description EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world's leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit . Role Title: Client-facing R&D Generative AI Architect BU/Segment: Digital Location: London, United Kingdom (Flexible hybrid working) Employment Type: Permanent Summary of the role We are seeking a visionary and technically adept Assistant Vice President (AVP) in EXL's AI Innovation & R&D team to spearhead our innovative client-facing initiatives in the rapidly evolving fields of Generative and Agentic AI. This high-impact, senior consulting role requires a unique blend of deep technical expertise in AI solutioning and deployment, Fortune 500 client stakeholder management skills, and the ability to drive thought leadership. You will be instrumental in advising Insurance, Healthcare, and Banking clients, designing cutting-edge AI solutions, leading complex implementations, and shaping EXL's strategy and market presence in Generative and Agentic AI. You will collaborate closely with data science, technology, business development, and client teams to identify opportunities, architect robust solutions, and deliver transformative results. As part of your duties, you will be responsible for: AI Architecture Innovation Research & Design: Focus on new innovative methods of designing and architecting AI and GenAI systems and be able to grasp and adapt monthly and weekly AI innovation coming out in the industry and apply it to our clients' use cases and needs in new modern ways. Client Advisory & Solutioning: Engage directly with senior client stakeholders (including C suite) to understand complex business challenges, identify opportunities for GenAI and Agentic AI, and define project scope. Workshop Facilitation: Design, lead, and facilitate high-impact client workshops and strategy sessions focused on identifying and prioritizing Generative and Agentic AI use cases and roadmap development. Technical Leadership & Architecture: Design, architect, and oversee the development and deployment of scalable, robust, and cutting edge Generative AI and sophisticated Agentic AI systems (including multi agent workflows) for client and internal projects. Project & Engagement Leadership: Lead large scale, complex Generative AI and Agentic AI projects from strategic conception through successful deployment, managing cross functional teams (internal and client side) and ensuring timely delivery of high quality solutions. Technical Mentorship: Mentor and guide technical teams (data scientists, data and AI engineers) in best practices for advanced AI development, deployment, MLOps/LLMOps, and agentic system design. Stakeholder Management: Build and maintain strong relationships with key internal and external stakeholders, effectively communicating complex technical concepts and project progress. Quality & Best Practices: Ensure adherence to rigorous software engineering principles, Agile methodologies, and responsible AI practices throughout the solution lifecycle. Stay Current: Maintain deep expertise in the latest trends, research, tools, and technologies within Generative AI, Large Language Models (LLMs), and Agentic AI paradigms. Qualifications and experience we consider to be essential for the role Programming & Libraries: Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). AI driven SDLC: Claude Code, Codex. Experience using Cursor, Windsurf, Replit, and Github Copilot. Google Stitch. LLM Expertise: Proven experience developing applications leveraging state of the art LLMs (e.g., GPT series, Llama series, Mistral, Claude) including prompt engineering, fine tuning, and evaluation. GenAI & Agentic Frameworks: Hands on mastery of core GenAI frameworks (e.g., LangChain, LlamaIndex, Langfuse) and practical experience with Agentic AI frameworks and concepts (e.g., AutoGen, CrewAI, LangGraph, OpenClaw, NemoClaw, agent planning, tool use integration, multi agent collaboration). AI Architecture: Deep understanding of AI/ML system architecture patterns, including microservices, event driven architectures, and patterns specific to RAG (Retrieval Augmented Generation), Graph RAG, Agentic RAG, and multi agent systems. Data: Knowledge of industry approaches to data engines and data labeling like Scale.ai and Mercor. Experience with auto data labeling and synthetic data generation techniques. Vector Databases & Embeddings: Expertise in working with various embedding models and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS). Advanced AI Concepts: Strong grasp of advanced techniques such as complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for complex AI systems. Software Engineering: Strong foundation in software engineering principles for building scalable, maintainable, and production ready AI systems. Cloud Platforms: Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS, Azure, GCP), including their AI/ML services. LLMOps/MLOps: Expertise in designing and implementing robust MLOps/LLMOps pipelines for automated testing, CI/CD, monitoring, and governance of complex AI models and applications. Leadership & Communication Proven ability to lead and motivate diverse, global teams Excellent communication skills, capable of explaining complex AI concepts to various stakeholders Strong project and program management skills and experience working in Agile environments Qualifications Education: Bachelor's degree in Computer Science, AI, Machine Learning, or a related quantitative field. Master's or Ph.D. strongly preferred. Experience: Minimum 10 years of experience in AI/ML/Data Science, with at least 5 years in significant leadership roles involving solution architecture, team management, and project delivery. Deployment Success: Demonstrated track record of successfully architecting and deploying large scale AI projects, preferably including complex GenAI and/or Agentic AI applications in enterprise or client settings. Consulting Background: Prior experience in technology consulting or a client facing technical specialist role within a technology provider is highly advantageous. Global Experience: Experience working effectively with global teams across multiple geographic locations is a plus. As part of a leading global Data and AI company, you can look forward to: A competitive salary with a generous bonus, private healthcare, critical illness life assurance at 4x your annual salary, income protection insurance, and a rewarding pension. EXL provides everyday financial well being solutions, such as cash back cards, in which you can earn cashback while enjoying discounts, promotions, and offers from top retailers. We also offer a Cycle Scheme where you can save money on bikes and cycling accessories. At EXL, we are committed to providing our employees with the tools and resources they need to succeed and excel in their careers. We offer a wide range of professional and personal development opportunities. We also support a range of learning initiatives that allow our employees to build on their existing skills and knowledge. From online courses to seminars and workshops, our employees have the opportunity to enhance their skills and stay up to date with the latest trends and technologies. As an Equal Opportunity Employer, EXL is committed to diversity. Our company does not discriminate based on race, religion, colour, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, age, or disability status. EXL employees are eligible to purchase stock as part of our Employee Stock Purchase Plan (ESPP). At EXL, we offer a flexible hybrid working model that allows employees to live a balanced, healthy lifestyle while strengthening our culture of collaboration. To be considered for this role, you must already be eligible to work in the United Kingdom.
21/05/2026
Full time
Client-facing R&D Generative AI Architect Trending Job Info Job Identification 11937 Posting Date 03/26/2026, 11:20 AM Job Role AI Engineer-AI Solutions Architect Experience (In Years) 6-9 Job Location London Job Description EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world's leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit . Role Title: Client-facing R&D Generative AI Architect BU/Segment: Digital Location: London, United Kingdom (Flexible hybrid working) Employment Type: Permanent Summary of the role We are seeking a visionary and technically adept Assistant Vice President (AVP) in EXL's AI Innovation & R&D team to spearhead our innovative client-facing initiatives in the rapidly evolving fields of Generative and Agentic AI. This high-impact, senior consulting role requires a unique blend of deep technical expertise in AI solutioning and deployment, Fortune 500 client stakeholder management skills, and the ability to drive thought leadership. You will be instrumental in advising Insurance, Healthcare, and Banking clients, designing cutting-edge AI solutions, leading complex implementations, and shaping EXL's strategy and market presence in Generative and Agentic AI. You will collaborate closely with data science, technology, business development, and client teams to identify opportunities, architect robust solutions, and deliver transformative results. As part of your duties, you will be responsible for: AI Architecture Innovation Research & Design: Focus on new innovative methods of designing and architecting AI and GenAI systems and be able to grasp and adapt monthly and weekly AI innovation coming out in the industry and apply it to our clients' use cases and needs in new modern ways. Client Advisory & Solutioning: Engage directly with senior client stakeholders (including C suite) to understand complex business challenges, identify opportunities for GenAI and Agentic AI, and define project scope. Workshop Facilitation: Design, lead, and facilitate high-impact client workshops and strategy sessions focused on identifying and prioritizing Generative and Agentic AI use cases and roadmap development. Technical Leadership & Architecture: Design, architect, and oversee the development and deployment of scalable, robust, and cutting edge Generative AI and sophisticated Agentic AI systems (including multi agent workflows) for client and internal projects. Project & Engagement Leadership: Lead large scale, complex Generative AI and Agentic AI projects from strategic conception through successful deployment, managing cross functional teams (internal and client side) and ensuring timely delivery of high quality solutions. Technical Mentorship: Mentor and guide technical teams (data scientists, data and AI engineers) in best practices for advanced AI development, deployment, MLOps/LLMOps, and agentic system design. Stakeholder Management: Build and maintain strong relationships with key internal and external stakeholders, effectively communicating complex technical concepts and project progress. Quality & Best Practices: Ensure adherence to rigorous software engineering principles, Agile methodologies, and responsible AI practices throughout the solution lifecycle. Stay Current: Maintain deep expertise in the latest trends, research, tools, and technologies within Generative AI, Large Language Models (LLMs), and Agentic AI paradigms. Qualifications and experience we consider to be essential for the role Programming & Libraries: Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). AI driven SDLC: Claude Code, Codex. Experience using Cursor, Windsurf, Replit, and Github Copilot. Google Stitch. LLM Expertise: Proven experience developing applications leveraging state of the art LLMs (e.g., GPT series, Llama series, Mistral, Claude) including prompt engineering, fine tuning, and evaluation. GenAI & Agentic Frameworks: Hands on mastery of core GenAI frameworks (e.g., LangChain, LlamaIndex, Langfuse) and practical experience with Agentic AI frameworks and concepts (e.g., AutoGen, CrewAI, LangGraph, OpenClaw, NemoClaw, agent planning, tool use integration, multi agent collaboration). AI Architecture: Deep understanding of AI/ML system architecture patterns, including microservices, event driven architectures, and patterns specific to RAG (Retrieval Augmented Generation), Graph RAG, Agentic RAG, and multi agent systems. Data: Knowledge of industry approaches to data engines and data labeling like Scale.ai and Mercor. Experience with auto data labeling and synthetic data generation techniques. Vector Databases & Embeddings: Expertise in working with various embedding models and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS). Advanced AI Concepts: Strong grasp of advanced techniques such as complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for complex AI systems. Software Engineering: Strong foundation in software engineering principles for building scalable, maintainable, and production ready AI systems. Cloud Platforms: Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS, Azure, GCP), including their AI/ML services. LLMOps/MLOps: Expertise in designing and implementing robust MLOps/LLMOps pipelines for automated testing, CI/CD, monitoring, and governance of complex AI models and applications. Leadership & Communication Proven ability to lead and motivate diverse, global teams Excellent communication skills, capable of explaining complex AI concepts to various stakeholders Strong project and program management skills and experience working in Agile environments Qualifications Education: Bachelor's degree in Computer Science, AI, Machine Learning, or a related quantitative field. Master's or Ph.D. strongly preferred. Experience: Minimum 10 years of experience in AI/ML/Data Science, with at least 5 years in significant leadership roles involving solution architecture, team management, and project delivery. Deployment Success: Demonstrated track record of successfully architecting and deploying large scale AI projects, preferably including complex GenAI and/or Agentic AI applications in enterprise or client settings. Consulting Background: Prior experience in technology consulting or a client facing technical specialist role within a technology provider is highly advantageous. Global Experience: Experience working effectively with global teams across multiple geographic locations is a plus. As part of a leading global Data and AI company, you can look forward to: A competitive salary with a generous bonus, private healthcare, critical illness life assurance at 4x your annual salary, income protection insurance, and a rewarding pension. EXL provides everyday financial well being solutions, such as cash back cards, in which you can earn cashback while enjoying discounts, promotions, and offers from top retailers. We also offer a Cycle Scheme where you can save money on bikes and cycling accessories. At EXL, we are committed to providing our employees with the tools and resources they need to succeed and excel in their careers. We offer a wide range of professional and personal development opportunities. We also support a range of learning initiatives that allow our employees to build on their existing skills and knowledge. From online courses to seminars and workshops, our employees have the opportunity to enhance their skills and stay up to date with the latest trends and technologies. As an Equal Opportunity Employer, EXL is committed to diversity. Our company does not discriminate based on race, religion, colour, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, age, or disability status. EXL employees are eligible to purchase stock as part of our Employee Stock Purchase Plan (ESPP). At EXL, we offer a flexible hybrid working model that allows employees to live a balanced, healthy lifestyle while strengthening our culture of collaboration. To be considered for this role, you must already be eligible to work in the United Kingdom.
Are you a senior engineer who thrives on enabling teams to deliver faster, safer, and more consistently? Dizplai is seeking an experienced and hands on Lead Platform Engineer to join our growing engineering team. This is a senior, enablement focused role where you'll shape and improve the shared platform capabilities that help our squads deliver with speed and confidence. You'll lead the evolution of our AWS and engineering foundations, covering cloud infrastructure, account and environment management, deployment patterns, security guardrails, observability, automation, and developer experience. You'll combine deep technical expertise with broad organisational influence, helping set the direction for how we build, operate, and scale software reliably. A key part of this role is ensuring our organisation is set up to adopt AI safely, efficiently, and at scale. You'll define the right tooling, controls, reusable patterns, and platform standards so teams can use AI effectively without compromising security, quality, compliance, or cost. This isn't about becoming a delivery bottleneck or gatekeeper. It's about enabling squads through strong reusable foundations, sensible standards, strategic platform leadership, and practical support. Key Responsibilities Shape Platform Strategy & Foundations: Define and drive the platform engineering strategy in line with business, technology, security, and delivery goals. Design, build, and evolve shared platform capabilities that support product and delivery teams, reducing duplication through sensible standardisation, automation, and internal platform tooling. Lead AWS Platform Enablement: Own and improve AWS platform patterns across accounts, environments, access models, and organisational guardrails. Define repeatable cloud approaches for infrastructure, identity, networking, secrets, compute, and storage, helping teams operate safely and efficiently without slowing delivery. Enable Safe, Fast Delivery at Scale: Improve the platform so squads can ship changes with greater speed and confidence. Support deployment patterns, release workflows, and engineering guardrails that reduce risk and improve consistency. Build self service capabilities where the preferred approach is the easiest to use. Enable AI First Engineering Safely: Create the platform foundations that allow teams to adopt AI effectively across engineering and operational workflows. Establish reusable approaches for AI services, model integrations, and agent based workflows, supporting safe and scalable AI usage through strong patterns for access, governance, and cost awareness. Strengthen Security, Observability & Operational Readiness: Improve platform standards across security, CI/CD, observability, reliability, and operational readiness. Embed secure by default and operable by default patterns into engineering workflows, improving logging, metrics, alerting, tracing, and production visibility across teams. Improve Developer Experience & Engineering Culture: Reduce friction in day to day engineering workflows by improving tooling, automation, templates, and platform usability. Promote a culture of enablement, shared ownership, and continuous improvement, helping embed a platform mindset where common problems are solved once and reused widely. About You Strong hands on experience in platform engineering, DevOps, cloud infrastructure, or SRE style work. Strong practical AWS experience across infrastructure, IAM, networking, deployment patterns, and environment management, including supporting AWS account structures, access models, and cloud guardrails across multiple teams or environments. Experience building and improving CI/CD pipelines, infrastructure as code, and shared engineering tooling. Good understanding of observability, monitoring, alerting, and production operations, alongside practical knowledge of security, secrets management, secure delivery, and operational controls. Experience improving developer experience, standards, or engineering workflows across teams, with a good understanding of how platform design can enable safe and efficient AI adoption. Experience influencing technical direction, engineering practice, or platform strategy across teams, with strong collaboration skills, technical judgment, systems thinking, and organisational awareness. Desirable: experience with AWS Organisations, multi account environments, Control Tower, and SCPs; self service platform patterns and reusable internal templates; reliability engineering, incident management, and FinOps practices; enabling AI or ML tooling, model integrations, or LLM based workflows; familiarity with Team Topologies and enabling team principles.
21/05/2026
Full time
Are you a senior engineer who thrives on enabling teams to deliver faster, safer, and more consistently? Dizplai is seeking an experienced and hands on Lead Platform Engineer to join our growing engineering team. This is a senior, enablement focused role where you'll shape and improve the shared platform capabilities that help our squads deliver with speed and confidence. You'll lead the evolution of our AWS and engineering foundations, covering cloud infrastructure, account and environment management, deployment patterns, security guardrails, observability, automation, and developer experience. You'll combine deep technical expertise with broad organisational influence, helping set the direction for how we build, operate, and scale software reliably. A key part of this role is ensuring our organisation is set up to adopt AI safely, efficiently, and at scale. You'll define the right tooling, controls, reusable patterns, and platform standards so teams can use AI effectively without compromising security, quality, compliance, or cost. This isn't about becoming a delivery bottleneck or gatekeeper. It's about enabling squads through strong reusable foundations, sensible standards, strategic platform leadership, and practical support. Key Responsibilities Shape Platform Strategy & Foundations: Define and drive the platform engineering strategy in line with business, technology, security, and delivery goals. Design, build, and evolve shared platform capabilities that support product and delivery teams, reducing duplication through sensible standardisation, automation, and internal platform tooling. Lead AWS Platform Enablement: Own and improve AWS platform patterns across accounts, environments, access models, and organisational guardrails. Define repeatable cloud approaches for infrastructure, identity, networking, secrets, compute, and storage, helping teams operate safely and efficiently without slowing delivery. Enable Safe, Fast Delivery at Scale: Improve the platform so squads can ship changes with greater speed and confidence. Support deployment patterns, release workflows, and engineering guardrails that reduce risk and improve consistency. Build self service capabilities where the preferred approach is the easiest to use. Enable AI First Engineering Safely: Create the platform foundations that allow teams to adopt AI effectively across engineering and operational workflows. Establish reusable approaches for AI services, model integrations, and agent based workflows, supporting safe and scalable AI usage through strong patterns for access, governance, and cost awareness. Strengthen Security, Observability & Operational Readiness: Improve platform standards across security, CI/CD, observability, reliability, and operational readiness. Embed secure by default and operable by default patterns into engineering workflows, improving logging, metrics, alerting, tracing, and production visibility across teams. Improve Developer Experience & Engineering Culture: Reduce friction in day to day engineering workflows by improving tooling, automation, templates, and platform usability. Promote a culture of enablement, shared ownership, and continuous improvement, helping embed a platform mindset where common problems are solved once and reused widely. About You Strong hands on experience in platform engineering, DevOps, cloud infrastructure, or SRE style work. Strong practical AWS experience across infrastructure, IAM, networking, deployment patterns, and environment management, including supporting AWS account structures, access models, and cloud guardrails across multiple teams or environments. Experience building and improving CI/CD pipelines, infrastructure as code, and shared engineering tooling. Good understanding of observability, monitoring, alerting, and production operations, alongside practical knowledge of security, secrets management, secure delivery, and operational controls. Experience improving developer experience, standards, or engineering workflows across teams, with a good understanding of how platform design can enable safe and efficient AI adoption. Experience influencing technical direction, engineering practice, or platform strategy across teams, with strong collaboration skills, technical judgment, systems thinking, and organisational awareness. Desirable: experience with AWS Organisations, multi account environments, Control Tower, and SCPs; self service platform patterns and reusable internal templates; reliability engineering, incident management, and FinOps practices; enabling AI or ML tooling, model integrations, or LLM based workflows; familiarity with Team Topologies and enabling team principles.
Role: Data & ML Engineer Location: Newcastle Upon Tyne Levels: Senior Analyst, Specialist Experience Level: 3+ years Please Note:Due to the nature of client work you will be undertaking, you will need to be willing to go through a Security Clearance (Including BPSS) process as part of this role, which requires 5+ years UK address history at the point of application. Hybrid Working: Please note - This role will require you to work from our Newcastle, Cobalt Business Park office for a minimum of 3 days per week Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. As a team: Our Advanced Technology Centre is a thriving technology and innovation hub from where we deliver high quality services to a number of private and public sector clients. You'll learn, grow and advance in an innovative culture that thrives on shared success, diverse ways of thinking and enables boundaryless opportunities that can drive your career in new and exciting ways. If you're looking for a challenging career working in a vibrant environment with access to training and a global network of experts, this could be the role for you. As part of our global team, you'll be working with cutting edge technologies and will have the opportunity to develop a wide range of new skills on the job. Role Overview As a Data & ML Engineer, you will design, build, and optimize scalable data pipelines and machine learning solutions. You'll work with client teams to deliver intelligent data products, leveraging modern cloud and AI technologies. Key Responsibilities Design and implement robust data pipelines and ML workflows using Python, SQL, Spark, and Databricks. Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments. Integrate data from diverse sources, including streaming and batch ingestion, using Azure Data Factory, GCP Dataflow and AWS services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform. Visualize and communicate insights using Power BI, Tableau, and PowerApps. Mentor junior engineers and contribute to internal knowledge sharing. Ensure solutions meet security, compliance, and performance standards. Core Data & AI Skills Python, SQL, Spark, Scala Machine Learning, NLP, Deep Learning, Prompt engineering, Agentic AI Data Architecture, Data Modelling, Data Engineering, Data Analysis DevOps & Engineering CI/CD and MLOps (Azure DevOps, GitHub actions, Jenkins, Kubeflow etc) Infrastructure as Code (Terraform, Ansible etc) Containers (Kubernetes, Docker etc) Certifications & Tools Data Visualisation and UI (Power BI, PowerApps, Tableau etc) Data Science Platforms (Databricks, Snowflake etc) Cloud certifications (Azure, AWS, GCP) Cloud Native Data Engineering (Azure Data Factory, AWS Glue, GCP Dataflow etc) Other Requirements At least 3 years experience with large-scale data challenges (big data, distributed systems) Hands on with Infrastructure as Code (Terraform, Ansible) Agile and Waterfall project experience Strong stakeholder management and communication skills Security and compliance awareness Desirable Experience in client-facing roles Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer) Experience mentoring or managing teams What's in it for you At Accenture in addition to a competitive basic salary, you will also have an extensive benefits package which includes 25 days' vacation per year, private medical insurance and 3 extra days leave per year for charitable work of your choice! Flexibility and mobility are required to deliver this role as there may be requirements to spend time onsite with our clients and partners to enable delivery of the first class services we are known for.
21/05/2026
Full time
Role: Data & ML Engineer Location: Newcastle Upon Tyne Levels: Senior Analyst, Specialist Experience Level: 3+ years Please Note:Due to the nature of client work you will be undertaking, you will need to be willing to go through a Security Clearance (Including BPSS) process as part of this role, which requires 5+ years UK address history at the point of application. Hybrid Working: Please note - This role will require you to work from our Newcastle, Cobalt Business Park office for a minimum of 3 days per week Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. As a team: Our Advanced Technology Centre is a thriving technology and innovation hub from where we deliver high quality services to a number of private and public sector clients. You'll learn, grow and advance in an innovative culture that thrives on shared success, diverse ways of thinking and enables boundaryless opportunities that can drive your career in new and exciting ways. If you're looking for a challenging career working in a vibrant environment with access to training and a global network of experts, this could be the role for you. As part of our global team, you'll be working with cutting edge technologies and will have the opportunity to develop a wide range of new skills on the job. Role Overview As a Data & ML Engineer, you will design, build, and optimize scalable data pipelines and machine learning solutions. You'll work with client teams to deliver intelligent data products, leveraging modern cloud and AI technologies. Key Responsibilities Design and implement robust data pipelines and ML workflows using Python, SQL, Spark, and Databricks. Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments. Integrate data from diverse sources, including streaming and batch ingestion, using Azure Data Factory, GCP Dataflow and AWS services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform. Visualize and communicate insights using Power BI, Tableau, and PowerApps. Mentor junior engineers and contribute to internal knowledge sharing. Ensure solutions meet security, compliance, and performance standards. Core Data & AI Skills Python, SQL, Spark, Scala Machine Learning, NLP, Deep Learning, Prompt engineering, Agentic AI Data Architecture, Data Modelling, Data Engineering, Data Analysis DevOps & Engineering CI/CD and MLOps (Azure DevOps, GitHub actions, Jenkins, Kubeflow etc) Infrastructure as Code (Terraform, Ansible etc) Containers (Kubernetes, Docker etc) Certifications & Tools Data Visualisation and UI (Power BI, PowerApps, Tableau etc) Data Science Platforms (Databricks, Snowflake etc) Cloud certifications (Azure, AWS, GCP) Cloud Native Data Engineering (Azure Data Factory, AWS Glue, GCP Dataflow etc) Other Requirements At least 3 years experience with large-scale data challenges (big data, distributed systems) Hands on with Infrastructure as Code (Terraform, Ansible) Agile and Waterfall project experience Strong stakeholder management and communication skills Security and compliance awareness Desirable Experience in client-facing roles Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer) Experience mentoring or managing teams What's in it for you At Accenture in addition to a competitive basic salary, you will also have an extensive benefits package which includes 25 days' vacation per year, private medical insurance and 3 extra days leave per year for charitable work of your choice! Flexibility and mobility are required to deliver this role as there may be requirements to spend time onsite with our clients and partners to enable delivery of the first class services we are known for.
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 great thing. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analyse A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and model serving technologies (e.g., Tensorflow Serving, Triton, TorchServe). Experience with high volume data processing and real time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills. A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many subsidised cafés or restaurants on site. Settle in at your desk, check Slack for updates, then catch up with everyone at the team stand up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to the Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market leading video streaming services, underpinned by state of the art engineering principles. We do this at huge scale - for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch. The rewards 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 in the recruitment process. Your office space 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, cafés, 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. There's more to our work than work. We've built an inclusive culture where we can learn from each other and innovate together. There's plenty of opportunities for you to explore what you're passionate about.
21/05/2026
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 great thing. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analyse A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and model serving technologies (e.g., Tensorflow Serving, Triton, TorchServe). Experience with high volume data processing and real time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills. A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many subsidised cafés or restaurants on site. Settle in at your desk, check Slack for updates, then catch up with everyone at the team stand up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to the Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market leading video streaming services, underpinned by state of the art engineering principles. We do this at huge scale - for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch. The rewards 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 in the recruitment process. Your office space 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, cafés, 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. There's more to our work than work. We've built an inclusive culture where we can learn from each other and innovate together. There's plenty of opportunities for you to explore what you're passionate about.
Senior Data Scientist IIApplylocations: Farringdontime type: Full timeposted on: Posted 9 Days Agojob requisition id: R112250 Are you ready to take your data science expertise to the next level and lead impactful projects? Would you enjoy working on advanced machine learning models and cutting-edge analytics solutions? About our team: We are a fast-moving, high-impact Data Science & AI team building real-world GenAI and ML solutions across the entire LexisNexis business. Our work powers smarter decisions for Product, Sales, Finance, Marketing, Customer Success, and Engineering-everything from predictive models to enterprise GenAI apps to automation that transforms how teams operate.We are data science generalists who love variety. One day, it is designing a new GenAI workflow, the next it is deploying a model into Salesforce or engineering a pipeline in Databricks. We own our projects end-to-end and partner directly with stakeholders to deliver solutions that get used and make a measurable difference.If you want to experiment, build, ship, and see your work drive real impact across a global organisation, you will feel right at home with us. About the role: We are seeking a Senior Data Scientist II who is a Data Science Generalist. The ideal candidate is comfortable working across GenAI, traditional machine learning, analytics, data engineering, cloud platforms, and enterprise system integrations.In this role, you will design, build, and deploy AI and ML solutions that support key business functions across Product, Sales, Finance, Marketing, Customer Success, and Engineering. You will work end-to-end across ideation, modelling, experimentation, prompt engineering, deployment, monitoring, and stakeholder communication.This position is ideal for a versatile data scientist who enjoys solving diverse problems, working with multiple systems, and driving measurable business impact. Responsibilities: Build GenAI applications using OpenAI APIs, embeddings, vector search, and retrieval-augmented generation (RAG). Design advanced prompt engineering patterns and automated evaluation frameworks for LLM quality and safety. Develop and deploy traditional ML models (e.g., churn, propensity, sentiment/feedback, lead scoring, customer intelligence). Own the end-to-end model lifecycle: data prep, experimentation, deployment, and monitoring. Build and optimize feature pipelines and scoring jobs using Python, Databricks, Spark, Delta Lake, and AWS. Use AWS services (S3, Redshift, Lambda) for data automation, orchestration, and scalable processing. Ensure data quality, observability, lineage, and documentation across data and ML pipelines. Deliver enterprise integrations with Salesforce (SFDC) and Oracle platforms (Fusion, Service Cloud, Peoplesoft) for batch and real-time workflows. Create analytics solutions with cross-functional partners: define KPIs, connect customer/product/finance/CRM data, and drive actionable recommendations. Productionise reliably: provide L2/L3 support, monitor drift/data quality/prompt performance, run root-cause analysis, and implement preventative fixes. Requirements: Strong Python programming skills. Direct experience with OpenAI APIs, LLM workflows, and prompt engineering. Solid machine learning fundamentals, including supervised learning, NLP, and feature engineering. Experience with Databricks, Spark, and Delta Lake. Strong SQL skills with experience working on large datasets. Experience with AWS, including S3 and Lambda. Familiarity with Redshift, Snowflake, or other cloud data warehouses. Experience with behavioral datasets. Ability to work across machine learning, data engineering, analytics, and integrations. Ability to design end-to-end solutions spanning data, models, APIs, and automation workflows. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here . Please read our Candidate Privacy Policy.We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
21/05/2026
Full time
Senior Data Scientist IIApplylocations: Farringdontime type: Full timeposted on: Posted 9 Days Agojob requisition id: R112250 Are you ready to take your data science expertise to the next level and lead impactful projects? Would you enjoy working on advanced machine learning models and cutting-edge analytics solutions? About our team: We are a fast-moving, high-impact Data Science & AI team building real-world GenAI and ML solutions across the entire LexisNexis business. Our work powers smarter decisions for Product, Sales, Finance, Marketing, Customer Success, and Engineering-everything from predictive models to enterprise GenAI apps to automation that transforms how teams operate.We are data science generalists who love variety. One day, it is designing a new GenAI workflow, the next it is deploying a model into Salesforce or engineering a pipeline in Databricks. We own our projects end-to-end and partner directly with stakeholders to deliver solutions that get used and make a measurable difference.If you want to experiment, build, ship, and see your work drive real impact across a global organisation, you will feel right at home with us. About the role: We are seeking a Senior Data Scientist II who is a Data Science Generalist. The ideal candidate is comfortable working across GenAI, traditional machine learning, analytics, data engineering, cloud platforms, and enterprise system integrations.In this role, you will design, build, and deploy AI and ML solutions that support key business functions across Product, Sales, Finance, Marketing, Customer Success, and Engineering. You will work end-to-end across ideation, modelling, experimentation, prompt engineering, deployment, monitoring, and stakeholder communication.This position is ideal for a versatile data scientist who enjoys solving diverse problems, working with multiple systems, and driving measurable business impact. Responsibilities: Build GenAI applications using OpenAI APIs, embeddings, vector search, and retrieval-augmented generation (RAG). Design advanced prompt engineering patterns and automated evaluation frameworks for LLM quality and safety. Develop and deploy traditional ML models (e.g., churn, propensity, sentiment/feedback, lead scoring, customer intelligence). Own the end-to-end model lifecycle: data prep, experimentation, deployment, and monitoring. Build and optimize feature pipelines and scoring jobs using Python, Databricks, Spark, Delta Lake, and AWS. Use AWS services (S3, Redshift, Lambda) for data automation, orchestration, and scalable processing. Ensure data quality, observability, lineage, and documentation across data and ML pipelines. Deliver enterprise integrations with Salesforce (SFDC) and Oracle platforms (Fusion, Service Cloud, Peoplesoft) for batch and real-time workflows. Create analytics solutions with cross-functional partners: define KPIs, connect customer/product/finance/CRM data, and drive actionable recommendations. Productionise reliably: provide L2/L3 support, monitor drift/data quality/prompt performance, run root-cause analysis, and implement preventative fixes. Requirements: Strong Python programming skills. Direct experience with OpenAI APIs, LLM workflows, and prompt engineering. Solid machine learning fundamentals, including supervised learning, NLP, and feature engineering. Experience with Databricks, Spark, and Delta Lake. Strong SQL skills with experience working on large datasets. Experience with AWS, including S3 and Lambda. Familiarity with Redshift, Snowflake, or other cloud data warehouses. Experience with behavioral datasets. Ability to work across machine learning, data engineering, analytics, and integrations. Ability to design end-to-end solutions spanning data, models, APIs, and automation workflows. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here . Please read our Candidate Privacy Policy.We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
