76 to 100 of 160 Feature Engineering Jobs in the UK

hear from you. Benefits of the programme: Earn a salary while studying for your qualification Gain hands-on experience in a real AI and engineering environment Receive job-specific training and development Achieve a recognised Level 6 qualification Secure a permanent role from the start of your apprenticeship Have … knowledge, practical skills and professional behaviours needed to design, build, test and deploy dependable AI-enabled solutions. Working as part of our AI and engineering community, you will contribute to live projects across the machine learning lifecycle, collaborating with software, data, systems and domain specialists to turn needs into ...

post-quantum cryptography. You will lead the architecture behind: continuous trust decisioning shared signals and federation (CAEP/RISC/SET) streaming pipelines and feature stores behavioural intelligence systems Identity Assurance Graphs AI-agent and workload identity evaluation You’ll work across Ditto Verify, Authenticate, and Protect, combining identity … someone with: 10+ years in security, identity, fraud, risk, or trust architecture deep experience with real-time event-driven and streaming systems strong data-engineering and feature-engineering expertise experience building adaptive trust, behavioural intelligence, or signal-fusion platforms practical experience integrating AI/LLM systems into ...

with minimal supervision, and implement rigorous validation automation (such as backtesting and slice-based evaluation) to prevent data leakage, over-fitting, and production regressions. Engineering Partnership & Handovers: Collaborate closely with Engineering Leads to ensure compute/GPU infrastructure supports model requirements. Clearly define model failure modes, edge cases … build robust fallback systems. Applied Debugging & Guardrails: Diagnose complex algorithmic bugs and implement automated checks for "Silent Failures" (e.g., concept drift or production feature distribution shifts). Lead team-level post-mortems and resolve blocking corrective actions. Career Multiplier: Formally mentor mid-level and associate ML scientists, reviewing their ...

Barcelona, Milan, Edinburgh and Madrid. Now is a brilliant time to join us and help shape the future of travel. Introducing the Embedded Data Engineering in ML Team At the heart of our Data and ML teams, embedded Data Engineers create the pipelines and tables that power business critical … Machine Learning Engineers and Data Scientists to build reliable datasets for ML use cases. You'll also have access to Trainline's wider Data Engineering, Data Platform, and analytics community, working alongside other embedded Data Engineers in ML, including senior and principal engineers. In this role as the Embedded ...

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 … 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 ...

have missed. Develop and evaluate statistical and machine learning models. Build segmentation, propensity, forecasting and personalisation solutions that reach real customers. Apply rigour to feature engineering, validation and model performance. Design and evaluate experiments to understand genuine impact. Work with Data Engineering to create reliable model inputs ...

have missed. Develop and evaluate statistical and machine learning models. Build segmentation, propensity, forecasting and personalisation solutions that reach real customers. Apply rigour to feature engineering, validation and model performance. Design and evaluate experiments to understand genuine impact. Work with Data Engineering to create reliable model inputs ...

Data Science team is building a layered reliability platform that shifts CoreWeave from reactive troubleshooting to proactive reliability engineering. The platform spans telemetry ingestion, feature engineering, anomaly detection, failure prediction, distributed straggler detection, and agentic root cause analysis. As a forward deployed function, we partner closely with Fleet … intersection of data science and production systems, deploying advanced statistical models and machine learning methodologies directly within operational environments. You will collaborate closely with engineering and infrastructure teams to optimize GPU utilization, workload scheduling, and system efficiency in real time. You will design experiments, analyze large-scale system telemetry ...

client is a leading global investment bank. JOB DESCRIPTION We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III DevOps/AWS Engineer at our client within the Commercial & Investment Bank, particularly in the Payments … quality production code; review and debug code written by others to ensure reliability, performance, and maintainability. Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, accelerated test strategy, incident/root-cause ...

machine learning platforms. Data governance and metadata tooling to improve transparency, trust, and reuse across the organisation. Your Experience 5+ years experience in data engineering, building and maintaining scalable data platforms. Strong SQL and data modelling skills, with experience designing analytical datasets. Experience with modern data stack tools (e.g. … e.g. Cube.js) or metrics‐layer design. Exposure to data governance and metadata tools (e.g. OpenMetadata, Hive Metastore). Experience supporting machine learning workflows and feature engineering pipelines. Why This Role Matters This platform is central to how we enable trusted, scalable, and reusable data across sportsbook. It provides ...

models (not just consuming APIs) A solid understanding of model evaluation and validation, overfitting and bias/variance trade‐offs, and data quality and feature engineering Proficiency in Python and ML frameworks such as PyTorch or TensorFlow Experience building and maintaining ML pipelines in production Familiarity with ...

models (not just consuming APIs) A solid understanding of model evaluation and validation, overfitting and bias/variance trade-offs, and data quality and feature engineering Proficiency in Python and ML frameworks such as PyTorch or TensorFlow Experience building and maintaining ML pipelines in production Familiarity with ...

analytics, AI/ML capabilities and operational intelligence systems. This is an opportunity to work on technically challenging projects where you'll influence architecture, engineering approaches and the delivery of high-impact data capabilities. What You'll Be Doing Designing and developing modern data platforms and pipelines Building scalable … across data services Working closely with clients and multidisciplinary teams to solve complex data challenges What We're Looking For Commercial experience delivering Data Engineering solutions Strong Python and SQL skills, with experience of Java or Scala beneficial Experience building large-scale ETL/ELT and data processing pipelines ...

approaches (e.g. sequence prediction, intent modelling, imitation learning) into robust, production‐ready systems. Build and maintain end‐to‐end AI pipelines, including data ingestion, feature engineering, model training, inference, and monitoring. Apply causal inference techniques to evaluate the real‐world impact of AI‐driven decisions and support data … informed product changes. Integrate AI services into existing platforms via APIs, microservices, and event‐driven architectures in close collaboration with engineering teams. Partner with product and platform teams to ensure AI outputs are actionable, explainable, and aligned with business workflows. Support Digital Twin and agentic systems by implementing behavioural ...

Responsibilities: Develop and implement machine learning and AI models Develop test and evaluation protocols on ML/AI models Assist in data pre-processing, feature engineering, and exploratory data analysis Contribute to building scalable and maintainable AI software systems Debug, test, and improve existing models and codebases Document … soon as practical. About Us The National Physical Laboratory (NPL) is a world-leading centre of excellence that provides cutting-edge measurement science, engineering and technology to underpin prosperity and quality of life in the UK. NPL and DSIT have strong commitments to diversity and equality of opportunity ...

Azure, or Google Cloud. ✔️ Collaborate with cross-functional teams to define AI project goals. ✔️ Translate complex data insights into actionable business recommendations. ✔️ Perform feature engineering and data preprocessing. ✔️ Maintain clear documentation of models, datasets, and experiments. ✔️ Develop APIs for model integration with front-end systems. ✔️ Conduct peer code ...

such as Python, Java, or C++. • Strong understanding of machine learning frameworks and libraries (e.g.,TensorFlow, PyTorch, Scikit-learn). • Experience with data preprocessing, feature engineering, and model evaluation techniques. • Ability to work with large datasets and cloud-based platforms (e.g., AWS, Azure). • Excellent problem-solving skills ...

investigate problems, test hypotheses and develop analytical solutions. Monitor production models, investigate changes in performance and identify opportunities for improvement. Undertake exploratory analysis, feature engineering, model development, testing and validation. Evaluate new modelling techniques, AI applications and external data sources through practical experimentation. Support the deployment and ongoing ...

Bring Hands‐on experience in data science or applied machine learning. Strong understanding of Generative AI, LLMs, and RAG principles. Experience with data mapping, feature engineering, and end‐to‐end ML lifecycle management. Proficiency across Microsoft's Azure AI and data ecosystem, with an eagerness to adopt Fabric ...

financial services (ideally Anti-Financial Crime/Screening) Experience building Natural Language Processing (NLP)/Machine Learning (ML)/Artificial Intelligence (AI) pipelines, including feature engineering, model training, evaluation and monitoring Experience with hyperparameter tuning at scale and experimentation frameworks Strong technical experience with SQL and Python; significant ...

supplier directory, and payments data sourcesDevelop secure, high-quality production code in Python, and review and debug code written by othersBuild data pipelines and feature engineering jobs on Databricks to prepare payments data for model training and agent retrievalContribute to the MLOps path for optimization and prediction models … agents and model servicesFoster a team culture of diversity, opportunity, inclusion, and respectRequired Qualifications, Capabilities, and Skills: Formal training or certification in software engineering concepts and applied experienceHands-on practical experience in system design, application development, testing, and operational stabilityProficiency in Python and coding in one or more additional ...

cycles to ensure all models maintain the high level of accuracy and reliability required for professional-grade execution. Cross Functional Integration: Work closely with Engineering and Product teams to ensure seamless delivery of these complex feeds into client workflows, while maintaining the integrity of our internal IP. Cricket & Betting … machine learning and statistics. Practical Experience: Proven track record (2+ years) of applying data science methods as part of end-to-end pipelines (feature engineering, model training, deployment, validation) to solve complex real-world problems in a professional environment. Programming Fluency: Strong programming skills in Python ...

based features (prompting, retrieval‐augmented generation, and simple agentic workflows) alongside more traditional ML models. Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them. Translate solution designs into clean, well‐documented, production‐minded code. Contribute to model evaluation … generative AI, including prompting and RAG. Familiarity with how AI agents are built and orchestrated. Strong Python and common data/ML libraries; good engineering habits. Clear communicator and collaborative team player. Ideally, you’ll also have, but not essential: Exposure to cloud AI platforms, Azure a plus. Experience ...

Join a pioneering biotechnology company where your data engineering expertise will help drive innovation in gene therapy and improve the lives of patients with rare diseases. R&D Partners is seeking a Scientific Data Engineer to join an ambitious biotechnology company specializing in gene therapy and rare diseases. This … solutions to improve access to operational and scientific data across the R&D organization. Support data analysis activities by performing data mining, data exploration, feature engineering, and contributing to AI/ML, statistical, and modeling projects alongside data scientists and laboratory scientists. Ensure data quality and integrity throughout ...

forecasting, behavioural signals, and prediction, ensuring they are accurate, explainable, resilient, and regulator-ready. Own the full model lifecycle from problem framing, data exploration, feature engineering, back-testing, validation, deployment, monitoring, tuning, and incident response when models degrade or fail in production. Partner closely with engineering, data … Strong hands‐on technical skills, with the ability to work directly with data, code, ML frameworks, and complex datasets, while partnering effectively with software engineering and platform teams. Experience building scalable, reliable, and explainable AI/ML solutions that meet operational, governance, and regulatory requirements and deliver measurable business ...