51 to 75 of 102 Feature Engineering Jobs in the UK

increasingly sophisticated threat landscape. The Security Data and AI lab within the Chief Security Office is at the forefront of this transformation - engineering data platforms and AI-driven capabilities that enable intelligent, proactive defence.We're looking for a Lead Data Engineer to shape and lead the lab’s data … engineering capability. This is a senior role combining deep technical expertise with leadership, influencing direction and delivering high-impact outcomes across a complex enterprise environment. You’ll operate at the intersection of data engineering, security and AI, defining and driving the data engineering strategy and roadmap, owning ...

iterating on models before production deployment.Develop robust ML pipelines using AWS services and MLOps tooling.Implement experiment tracking, model versioning, monitoring, and reproducibility best practices.Build feature engineering pipelines and contribute to feature store development.Monitor production models, optimise performance, and drive continuous improvements.Apply Responsible AI principles, including explainability, governance … both technical and non-technical stakeholders.Desirable ExperienceAI agents and agentic workflows.Vector databases such as Pinecone, Weaviate, or pgvector.Feature stores including Feast or AWS Feature Store.Docker, Kubernetes, or Amazon ECS.Infrastructure as Code using Terraform or CloudFormation.Big data processing technologies such as Spark or Dask.Experience working within regulated or highly secure ...

offer . About the role: Join us as a Senior Software Engineer in our critical Account Integrity team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base. How we work … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product. What do you need? Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. System Design & Operation: Proven experience designing and operating CI/ ...

seeking to hire experienced Lead GenAI System Architect(s) in the AI Institute, which is a centre of excellence in Deloitte's Engineering, AI & Data service offering.You will be working with clients and other third parties, as well as Deloitte teams from across the Firm. You will have … deliver transformative AI and Generative AI strategies aligned with business goals.Lead the design, development, and implementation of advanced AI pipelines, encompassing data acquisition, preprocessing, feature engineering, model development, evaluation, and secure deployment at scale.Oversee the development and operationalisation of state-of-the-art AI models, including large language ...

understand business requirements and translate them into robust AI solutions.Design, develop, and implement end-to-end AI pipelines, including data acquisition, pre-processing, feature engineering, model training, evaluation, and deployment.Build and maintain scalable and efficient AI models using machine learning, deep learning, and other advanced analytics techniques.Stay abreast … want to help solve some of the biggest tech and transformational challenges around, join us. Together, we’ll make an impact that matters. Engineering, AI and DataWe lead transformation at the heart of our clients; re-engineering the core of our clients’ organisations, helping to unleash growth ...

offer.Job DescriptionJob DescriptionAbout the role:Join us as a Senior Software Engineer in our critical Account Integrity team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base.How we work:The Account … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product.What do you need Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. Experience building and designing scalable web applications that handle large amounts ...

projects end to end, from problem discovery and technical design through to delivery and measuring impact. Collaborate with Product, Compliance, Operations and other engineering teams while maintaining high standards for reliability, testing and code quality. What do you need? A strong product mindset and passion for user experience … understanding of JDBC and database internals. Experience with CI/CD pipelines and Distributed and Concurrent Systems Experience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plus Being able to work independently on customer problems ...

using distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems.Mentor junior team members and utilise model explainability methods to drive feature performance improvements.About You5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale business problems.Deep understanding of frequentist … Bayesian statistics, plus supervised and unsupervised modelling techniques.Proven experience modelling complex interactions (e.g., cluster or network effects).Expertise in model explainability to tune feature engineering and understand feature interactions.Ability to write high-quality, production-grade Python code and collaborate effectively with non-technical stakeholders.Proficient in leveraging LLMs ...

Your Impact Customer Onboarding & Engine Customization: Lead the technical deployment of our engines for new clients. Partner closely with customers, Customer Success, Product, and Engineering to adapt and customize ML models, ensuring they accurately reflect client-specific business logic, operational guardrails, and unique data nuances.Analytic Engine Development: Design … implement robust Machine Learning (LightGBM, XGBoost) and Deep Learning (PyTorch) models specifically focused on complex demand sensing and resolving cold-start forecasting problems. Feature Engineering Pipelines: Build and optimize scalable data pipelines leveraging a hybrid SQL/Python architecture (dbt, Snowflake) to extract rich, localized temporal signals from ...

concept into production environments Develop scalable ML pipelines using AWS cloud technologies Implement MLOps and LLMOps best practices for deployment, monitoring and governance Support feature engineering, model optimisation and performance monitoring Apply responsible AI principles, including model explainability and fairness Present findings and recommendations to technical … tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering and RAG architectures Experience with LLMOps tools such as LangChain, LangSmith or LangGraph Strong understanding of model monitoring, validation and governance Excellent communication ...

full delivery lifecycle, from early ideas through to production systems that create measurable impact for our customers and the business. As MLOps Engineering Manager, you will help shape how we build, deploy and operate machine learning products at scale, working closely with ML Engineers, Data Engineers, Software Engineers, Data … Scientists, Product Managers and stakeholders across Trainline.In this role as the MLOps Engineering Manager, you will... Build and lead a new team of MLOps Engineers, creating an environment where people can do their best work while delivering meaningful outcomes for customers and the business.Define and evolve MLOps processes, tooling ...

Azure and Databricks to help build, optimise, and scale Clarion’s modern data platform. You’ll be central to delivering a robust, high-performing engineering foundation that powers analytics, operational data flows, and future AI capabilities across our global events and digital products.This role is primarily focused on engineering … well-modelled data is available for analytics and future AI use cases.Assist with productionising ML pipelines where needed, ensuring they run reliably within Databricks.Support feature engineering and experiment environments as part of the wider platform.Work cross-functionally with product, marketing, operations, and technology teams to understand data needs ...

customer friction.Own projects end to end, from problem discovery and technical design through to delivery and measuring impact.Collaborate with Product, Compliance, Operations and other engineering teams while maintaining high standards for reliability, testing and code quality.What do you need A strong product mindset and passion for user experience … deep understanding of JDBC and database internals.Experience with CI/CD pipelines and Distributed and Concurrent SystemsExperience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plusBeing able to work independently on customer problems ...

customer experience transformation by applying modern AI architecture in a secure, scalable, and responsible manner. This role collaborates closely with business leaders, product teams, engineering, and third-party partners to ensure data and AI investments deliver measurable value while meeting regulatory, operational, and security requirements.Main Duties/ResponsibilitiesStrategy & Architecture … senior leadership on AI strategy, feasibility and adoption paths.AI ArchitectureDefine architectural patterns and standards to support AI model lifecycle management, AI and data pipelines, feature engineering, and associated design artefacts.Architect and own enterprise-scale Generative AI platforms supporting multiple business use cases, including internal pilots, automation assistants, knowledge ...

integrate agent tools and APIs to connect agents with external services, databases, and internal systems, ensuring robust output parsing and error handling.Practice advanced prompt engineering and implement output validation and guardrails to reduce hallucinations.Design microservices-based architectures and orchestrate multi-step workflows; instrument agents for tracing, metrics, and feedback … experience with agent frameworks such as LangChain, CrewAI, AutoGen, LangGraph.Knowledge of generative models including transformers, GANs, VAEs, and diffusion models.Understanding of data preprocessing, feature engineering, and model/agent evaluation techniques.Familiarity with cloud platforms and containerization technologies.Strong problem-solving skills and ability to work independently and collaboratively.Effective communication ...

retries.Design and implement robust evaluation frameworks to systematically assess and measure the performance of AI agents across key operational metrics.Practice advanced prompt and context engineering (e.g., Chain-of-Thought, ReAct, function calling/tool-use prompts), implement output validation and guardrails to reduce hallucinations.Deploy scalable AI services to cloud … agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).Experience with generative models (transformers, GANs/VAEs; diffusion models a plus).Strong understanding of data preprocessing, feature engineering, and evaluation techniques.Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).Strong communication skills for both technical and non-technical ...

SageMaker and Bedrock. What you’ll doPartner with stakeholders across the business to explore high‐impact opportunities.Own the full lifecycle: problem framing, data discovery, feature engineering, modelling, evaluation, deployment, monitoring, and iteration.Build and productionize LLM features where appropriate (retrieval‐augmented generation, evaluation, safety guardrails, cost/latency optimization … AWS. Contribute to DS/ML standards: experimentation, model governance, documentation, and reproducibility.Mentor junior scientists, work with external contractors and collaborate closely with data engineering on pipelines and data quality.What you’ll bringA proven track record delivering projects in a Data Science or AI Experience deploying models to production ...

grow and advance. Accenture’s Data and AI practice covers the range of Data and AI skills, from Strategy, Data Science, Data Architecture, AI Engineering and Visual Insights. When combined with Accenture’s broader Strategy and Consulting practice, we are able to bring together the unique ability to drive … capabilities that empower analytics and AI teams.Assist senior leaders in shaping elements of the strategic direction for practice’s data science and data engineering ecosystem.Help assess generative AI proposals by reviewing feasibility, data requirements, model considerations, and integration with existing technology stacks.Collaborate with digital teams, architects, and stakeholders ...

Responsibilities:Lead the development, implementation, and end-to-end delivery of advanced machine learning models and algorithms to drive market operations initiatives.Partner with AI Engineering teams to ensure robust architecture design and deployment patterns for AI/ML models that align with business needs.Mentor and guide a team … tools for managing the machine learning lifecycle.Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.Strong understanding of data preprocessing, feature engineering, and evaluation techniques.Experience working with large, complex datasets and applying statistical analysis.Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker ...

Lead the development, implementation, and end-to-end delivery of advanced machine learning models and algorithms to drive market operations initiatives. Partner with AI Engineering teams to ensure robust architecture design and deployment patterns for AI/ML models that align with business needs. Mentor and guide a team … managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization ...

coherent, scalable, secure, and aligned with RELX Responsible AI standards.This is a senior individual-contributor role with broad influence. You will partner closely with Engineering Leads, Product Managers, Data Scientists, and data teams within LNIP.Key Responsibilities:Define and own the AI architecture vision for Protégé in PatentSight+, ensuring technical … patterns for AI-driven enrichment and classification of patent data at scale, ensuring results are dependable, auditable, and consistent with established IP metrics.Establish prompt engineering standards, evaluation harnesses, and quality frameworks to govern LLM behaviour and maintain output accuracy in production.Partner with Product Management to assess technical feasibility ...

scalable, secure, and aligned with RELX Responsible AI standards. This is a senior individual-contributor role with broad influence. You will partner closely with Engineering Leads, Product Managers, Data Scientists, and data teams within LNIP. Key Responsibilities: Define and own the AI architecture vision for Protégé in PatentSight+, ensuring … driven enrichment and classification of patent data at scale, ensuring results are dependable, auditable, and consistent with established IP metrics. Establish prompt engineering standards, evaluation harnesses, and quality frameworks to govern LLM behaviour and maintain output accuracy in production. Partner with Product Management to assess technical feasibility and shape ...

credit risk (e.g., underwriting and limit management), finance (provisioning, offloading, profitability), and other models, rigorously reviewing and challenging all aspects: conceptual soundness, data integrity, feature engineering and selection, training and testing, regulatory compliance and fairness, documentation, deployment, monitoring and business impact. Independently replicate the model development process where … practices. Who you are Advanced degree (Master’s or PhD) in a quantitative field such as data science, statistics, mathematics, computer science, physics, or engineering; or equivalent experience. 3+ years of hands-on experience in credit risk and/or IFRS9/CECL impairment modeling. Strong technical expertise ...

research-only environment. You'll work on real business problems, build machine learning models that drive decision-making, and collaborate closely with engineering teams to see your work deployed and used at scale. What you'll be doing: Partnering with stakeholders to turn business challenges into Data Science solutions … looking for: Commercial experience as a Data Scientist Strong Python and SQL skills Hands-on experience building Machine Learning models Expertise in feature engineering, model evaluation and model selection Experience working with large datasets Exposure to Azure, AWS or GCP Strong stakeholder management and communication skills Experience taking ...

Data Science team of a large, established financial services business. The company has invested in its data platform and is building a dedicated ML Engineering capability to get more models into production. You'll work on real business problems, using large and varied datasets to develop models that … initial experimentation. You should be comfortable with: Python and common data science libraries. SQL and working with large datasets. Statistical modelling and machine learning. Feature engineering, model selection and evaluation. Writing clear, maintainable and testable code. Git-based development workflows. Working in a cloud environment such as Azure ...