1 to 25 of 32 Permanent Feature Engineering Jobs in England

analytics environment. This role will focus on building and optimising SAS-based models, supporting the full model development lifecycle from data preparation and feature engineering through to testing, validation, and production deployment. Key Responsibilities Design, develop, and enhance statistical, predictive, and pricing models using SAS Build modelling datasets … feature engineering pipelines, and variable transformations Develop SAS programs using: o Base SAS o SAS Macros o Data Step o SAS SQL Support automated model execution, scoring, and monitoring processes Conduct model testing, validation, back-testing, and performance analysis Analyse large datasets to identify trends, patterns, and business ...

workflows, and develop containerised model services that integrate directly into the OneView platform. This includes hands‐on work with model architectures, feature engineering, model optimisation, performance debugging, schema‐aligned data preparation, and ML‐driven interfaces. This is a role for engineers who want to build and maintain real … real systems, and solve real operational ML problems – not just prototypes. You will work directly with production data, client technical teams, and our internal engineering ecosystem to deliver AI components that are robust, scalable, and deployed into live environments. Key Responsibilities Machine learning engineering Design, train and optimise ...

models by converting analysts' Python code into scalable, maintainable and deployable workflows Design, build and maintain data pipelines for pricing inputs, including ingestion, transformation, feature preparation and quality checks Build and automate workflows for elasticity, forecasting, optimisation and other pricing models Develop and manage API integrations, including competitor pricing … feeds and downstream systems Work closely with pricing analysts to translate pricing logic into production-ready processes Support model performance improvement through data preparation, feature engineering and data mining techniques Monitor production processes and model performance over time, recommending corrective action where required Ensure pricing models are deployed ...

performance using appropriate metrics. You will: Explore and visualise data to discover innovative features and potential data sources. Engineer datasets, develop data pipelines, perform feature engineering, and write code to train, deploy, monitor, and run real‐time inferences. Build and monitor ML models, addressing issues such as overfitting … underfitting, data leakage, and drift. You will use your expertise in engineering and DevOps/MLOps to manage our machine learning platforms using AWS SageMaker and other AWS services. You will: Design, build, and improve scalable public cloud‐based machine learning platforms. Develop robust data pipelines and workflows, contributing ...

stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline. We are looking for a Machine Learning Engineering Manager to join our team help shape the future of train travel. You will be part of a highly innovative AI and ML platform … enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users. As a Machine Learning Engineering Manager at Trainline you will... 🚄 Lead a high performing team of Machine Learning Engineers working alongside Software Engineers, Data Scientists, Data Engineers and Product Managers ...

systems that process high-volume, high-value data and increasingly leverage AI and automation to deliver measurable customer and business outcomes. We value pragmatic engineering, clear thinking, and continuous learning. Our teams are small, autonomous, and outcome-focused, with a strong emphasis on quality, ownership, and collaboration. … platform scalability, operational excellence and maturity, and cost-efficient growth to support our long-term strategy and enterprise ambitions. The Role AI Platform Architecture & Engineering Own the design, build, and evolution of Infinity’s AI platform - the infrastructure layer that underpins AI-driven product capability and AI-assisted engineering ...

technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards. You will contribute … compliance framework. This is a highly hands‐on, highly technical, principal‐level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps. Key Responsibilities Technical Leadership & Architecture Define the end‐to‐end ML architecture for the matching platform, including data pipelines, model training ...

position responsible for designing, building, and deploying enterprise-grade AI solutions that drive measurable business value across the organisation. Working closely with IT, Data, Engineering, and senior business stakeholders, you will lead the development and implementation of advanced AI solutions, leveraging Large Language Models (LLMs), Retrieval-Augmented Generation … expertise with strategic thinking, taking solutions from concept through to production deployment and adoption. The ideal candidate will have a strong foundation in AI Engineering combined with a robust Data Science background, enabling them to develop, evaluate, and optimise AI solutions that deliver measurable business outcomes. This role would ...

solutions and regulatory reporting — ensuring teams across the business can trust and use data with confidence. You’ll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you’ll define clear standards … self‐service analytics and AI/ML model consumption. Collaborate with ML Ops and Data Science teams to define data product standards and feature engineering patterns. Evaluate and lead adoption of emerging Azure and Databricks capabilities — including Microsoft Fabric, OneLake and DirectLake — where they advance the data architecture. ...

solutions and regulatory reporting — ensuring teams across the business can trust and use data with confidence. You’ll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you’ll define clear standards … self‐service analytics and AI/ML model consumption. Collaborate with ML Ops and Data Science teams to define data product standards and feature engineering patterns. Evaluate and lead adoption of emerging Azure and Databricks capabilities — including Microsoft Fabric, OneLake and DirectLake — where they advance the data architecture. ...

exploration into advanced techniques, including LLMs, RAG architectures, and Generative AI applications to create new forms of automated analysis and augmented intelligence products. Production Engineering & MLOps : Translate validated prototypes into robust, production‐ready specifications, and lead the implementation of MLOps best practices (CI/CD, monitoring, serving) required … reliable deployment of models. Complex Data & Feature Engineering : Deeply explore complex, multi‐modal data (e.g., high‐dimensional data, text, time series) defining the necessary features and data pipelines to support highly accurate experimental models for strategic analysis. Cross‐Functional Collaboration : Work closely with the Product Manager, Data Scientists ...

client‐facing LLM‐powered experiences used by business travelers worldwide. We are looking for a Machine Learning Engineer II to join our Product AI Engineering team. You will help us design, build, and optimize intelligent systems. This is not just a modeling role, you’ll own the full lifecycle … concepts and steps involved in working with real‐world large data sets: from domain‐specific problem understanding, data preparation, travel‐related data processing, feature engineering, data structures for ML, data pipelining, modeling, offline evaluation, online evaluation, and monitoring. Strong knowledge of hands‐on practice in Python. Familiarity with ...

Spring framework, 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. A strong product mindset and passion for user … work – a practical guide DEI @ Wise Wise Tech Stack (2025 update) See what it's like to work at Wise London! Our Engineering career map Wise Engineering – https://medium.com/wise-engineering What do we offer: Starting salary: £87,500 - £111,000 + RSUs Wise ...

models Collaborate with senior team members to define cognitive computing strategies and guide the full AI project lifecycle Conduct in‐depth exploratory data analysis, feature engineering, and model selection for structured and unstructured data Utilize advanced analytics techniques, including NLP and ML, to extract insights and drive decision ...

Company Ion recruitment Location Surrey, UK (Office based) Overview A global software company is evolving its core engineering platforms by embedding machine learning and applied AI into high‐performance simulation and modelling tools used worldwide. This is a hands‐on applied AI role — focused on building and deploying … solutions inside production‐grade engineering systems, not isolated research or experimental prototypes. Responsibilities Create, deploy, and maintain machine learning models in production engineering software systems. Own the full ML pipeline: data preparation, feature engineering, training, evaluation, and optimisation. Translate complex scientific/engineering problems into ...

Join our global Quantitative Trading & Research (QTR) team, where you’ll apply your expertise in Derivatives Modelling, Financial Engineering, Data Science, and Quantitative Development. As part of JP Morgan’s leading QTR Group, you’ll innovate with unique analytics and mathematical models, enhancing business practices through automation. We develop … limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...

limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best … resourcing via data‐driven analysis, scenario studies, and clear articulation of trade‐offs. Lead development of ML/AI solutions end‐to‐end (feature engineering, model training/validation, MLOps, monitoring and drift management) with rigorous controls, documented governance, and demonstrable business value. Uphold standards for documentation, reproducibility ...

Pega CDH adaptive models Strong MLB/RTIM/arbitration logic knowledge Advanced Python & ML development A/B testing, uplift measurement, model governance Feature engineering & real-time vs batch decisioning Git, Agile, cross-functional collaboration NBA Decisioning Specialist Deliver decisioning use cases and personalisation strategies. Key Skills ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

unlock new capabilities for our market-leading suite of trade surveillance products. This role will see you combine hands‐on model development and software engineering, and collaborate with a high-performing team of Quant Researchers and Developers as well as other cross-functional departments. Responsibilities Design, develop, and deploy … linear regression, reinforcement learning and deep learning Industry experience using Large Language Models (LLMs) to deliver commercial value Experience building data pipelines and performing feature engineering on real-world datasets Strong problem-solving skills and attention to detail Good understanding of SQL and working with complex datasets Keen ...

Must-haves 3+ years experience in data science Strong Python and SQL skills Experience building and evaluating predictive models Understanding of data modelling and feature engineering Ability to translate data into clear commercial insight and recommendations Confident communicator - comfortable working directly with clients Consultancy or client-facing experience ...