1 to 25 of 35 Permanent Feature Engineering Jobs in England

Consulting Firms. Our Solutions & AI Labs (SAIL) practice is looking for an experienced Senior Manager to lead consultancy engagements and grow our AI & Solutions Engineering capability. The Forward Deployed AI & Solutions Engineer role will lead the delivery of AI-enabled solutions embedded in our clients’ teams, combining deep technical … solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions. What you will be doing As a Senior Manager in SAIL, you will own and lead consultancy engagements ...

about leveraging cutting‐edge AI to transform financial markets? Do you thrive on building end‐to‐end solutions, from robust data pipelines and sophisticated feature engineering to deploying advanced predictive models and personalized recommendation systems? If you have hands‐on experience, and a desire to make a significant … graph databases and knowledge graphs, to generate deep insights into financial markets and enhance Marquee’s platform engagement. We collaborate closely with Sales, Trading, Engineering, Product, Design, other areas of the Global Markets Division, and directly with clients. Our global team comprises experts in financial markets, product structuring, cutting ...

Principal, AI/ML Engineer leads the design, delivery and continuous improvement of AI and ML solutions within their area of responsibility, aligning engineering activities to the Bank’s broader AI strategy and long‐term objectives. The role combines strong technical leadership with a clear focus on delivery outcomes … operates with a clear understanding of the wider technology landscape, contributing to strategic direction while taking accountability for translating this into practical, high‐quality engineering outcomes across squads. AI/ML Engineering Direction Leads the definition and execution of AI/ML engineering direction across ...

Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real business outcomes. You'll work across … lifecycle—from problem framing and data preparation through to model development, evaluation, deployment, monitoring and iteration. The role suits someone who pairs solid software engineering foundations with genuine ML rigour and a healthy scepticism about what models can and can't be trusted to do. Key Responsibilities Partner with ...

graph databases and knowledge graphs, to generate deep insights into financial markets and enhance Marquee’s platform engagement. We collaborate closely with Sales, Trading, Engineering, Product, Design, and other areas of the Global Markets Division, and directly with clients. Our global team comprises experts in financial markets, product structuring …/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies. RESPONSIBILITIES AND QUALIFICATIONS Responsibilities: Design, build, and maintain robust data pipelines for feature engineering and model training, ensuring data quality, scalability, and explainability. Develop, train, and deploy state‐of‐the‐art machine learning models, with ...

designing, building, deploying, and continuously improving production machine learning systems from end to end. You will own the full lifecycle of models, from feature engineering and training through deployment, monitoring, retraining, and ongoing optimisation, working independently while collaborating closely with engineering and product teams to deliver measurable … improvements to ensure models remain accurate and reliable. Design and run experiments, track results and use data to drive model improvements. Work closely with engineering and product teams to integrate models into production systems and deliver business value. Requirements Must have: 5+ years of experience building and deploying machine ...

designing, building, deploying, and continuously improving production machine learning systems from end to end. You will own the full lifecycle of models, from feature engineering and training through deployment, monitoring, retraining, and ongoing optimisation, working independently while collaborating closely with engineering and product teams to deliver measurable … improvements to ensure models remain accurate and reliable. Design and run experiments, track results and use data to drive model improvements. Work closely with engineering and product teams to integrate models into production systems and deliver business value. Requirements Must have: 5+ years of experience building and deploying machine ...

Python and SQL skills Experience developing and deploying machine learning models into production environments Excellent understanding of statistical modelling, experimentation, and model evaluation Strong feature engineering and exploratory data analysis capabilities Experience communicating technical findings and insights to non-technical stakeholders A degree qualification (BSc, MSc, PhD etc. … innovation The Senior Data Scientist role will involve: Developing and deploying machine learning models to solve real-world business challenges Performing exploratory data analysis, feature engineering, model development, and evaluation Building forecasting, classification, segmentation, and predictive modelling solutions Designing and executing statistical analyses and experiments to support strategic ...

generating, deploying and continuously improving bespoke machine learning models for every customer. You'll work with large-scale behavioural event data, applying machine learning, feature engineering and experimentation to improve prediction accuracy and drive measurable customer outcomes. Working alongside highly experienced founders and recognised experts in machine learning … business. Skills & Experience Strong commercial experience building machine learning models in Python Excellent understanding of predictive modelling, classification or propensity modelling Experience with feature engineering, model evaluation and experimentation Comfortable working across the full machine learning lifecycle Experience working with cloud platforms and modern ML tooling Curious ...

Description AI Forward Deployed Engineer Machine Learning, Python, PyTorch, TensorFlow, LLMs, RAG, Generative AI, Agentic Systems, Cloud, Consulting, Solutions Engineering, EMEA (Remote)Very Attractive Salary + BenefitsThis is a fantastic opportunity for a Senior AI Forward Deployed Engineer to join a leading technology consulting and AI delivery organisation, working … deploying Machine Learning systems in production environments is expected as an AI Forward Deployed Engineer, including full end-to-end pipelines covering data ingestion, feature engineering, model training, evaluation, and deployment. The AI Forward Deployed Engineer will bring strong practical experience in Generative AI and modern AI systems ...

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 ...

cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base … practical applications. You are proficient in SQL and database operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). ...

cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base … practical applications. You are proficient in SQL and database operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). ...

cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base … practical applications. You are proficient in SQL and database operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). ...

cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base … practical applications. You are proficient in SQL and database operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). ...

cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base … practical applications. You are proficient in SQL and database operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). ...

cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base … practical applications. You are proficient in SQL and database operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). ...

cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base … practical applications. You are proficient in SQL and database operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). ...

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 … operation of machine learning products, ensuring models and AI systems are production‐ready, observable and able to support Trainline’s growth. Partner closely with engineering, data science, product and data teams to bring strong engineering standards into machine learning delivery, while recognising the specific challenges of data ...

such as GANs and VAEs. Proven experience applying these techniques to real-world tasks (text, code, image, multimodal generation) and familiarity with advanced prompt engineering, structured outputs, function/tool calling, and orchestration frameworks like LangChain, LangGraph, LlamaIndex, and Semantic Kernel. Hands‐on exposure to API-based LLM providers … project management skills, overseeing timelines, milestones, and deliverables; coordinating internal teams and clients to ensure project success. Data Understanding : Foundational grasp of data preprocessing, feature engineering, and data quality assurance processes to support AI model requirements. Responsible AI & Governance : Awareness of AI governance, safety, and compliance considerations—data ...

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 ...

This is a senior individual contributor role with strong influence through mentorship, collaboration, and technical leadership. You will work closely with partners across product, engineering, and the business to design and deliver data‐driven solutions.We welcome candidates from a range of backgrounds and experiences who are excited to apply … Development** Lead by example through hands-on coding and model development. Design, prototype, and validate innovative solutions for high-impact problems. Partner with engineering teams to deploy models into production environments.* **Domain Expertise** Leverage deep knowledge of aviation, travel, or related industries to inform modeling approaches and deliver customer ...

Experience designing and operating modern data platforms Experience developing or enabling AI and machine learning capabilities using business data Strong understanding of data preparation, feature engineering and model evaluation Experience with Python-based data and ML tooling, e.g. Pandas, NumPy and scikit-learn Experience with ML tooling within ...

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. ...

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 ...