1 to 25 of 37 Permanent Feature Engineering Jobs in England

deliver production-grade ML systems for a leading digital gaming and gambling platform. This is a hands-on role combining data science expertise with engineering skills - you'll build models, optimise algorithms, and deploy solutions at scale to enhance customer engagement and decisioning. You'll work closely with Data … science & modelling: Develop, validate, and optimise predictive models using advanced ML algorithms (e.g., gradient boosting, logistic regression, ensemble methods). End-to-end ML engineering: Deploy models as APIs, batch jobs, and streaming services; implement CI/CD, monitoring, and rollback strategies. Feature engineering & pipelines: Build scalable ...

strongest teams in the business. Your Responsibilities Will Include: Designing, developing, and validating statistical models and machine‐learning solutions Conducting exploratory data analysis and feature engineering to uncover insights and support decision‐making Working closely with data engineers to ensure high‐quality, scalable data pipelines for modelling Translating … machine‐learning models Solid understanding of statistical methods, predictive modelling, and experimental design Experience working with large or complex datasets, including data cleansing and feature engineering Ability to communicate analytical concepts clearly to non‐technical stakeholders Experience working in an agile delivery environment Strong problem‐solving skills ...

building the future of population health management. As a Senior Machine Learning Engineer, you will sit at the intersection of data science, platform engineering, and production systems. Your mission is to design and operate the foundations that allow ML, analytics, and agentic AI systems to move safely and reliably … from experimentation into regulated healthcare production environments on Google Cloud Platform. You will be the primary interface between Data Science and Platform Engineering, enabling rapid iteration while enforcing production and compliance standards. Responsibilities Design and implement Onsera's agentic AI platform – architect LLM/agent framework selection, standardized patterns ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring. Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails. Design feature engineering approaches and contribute to feature store development. Support production models through monitoring, performance analysis, and continuous improvement. Apply responsible AI practices … governance and quality controls. Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC). Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures. Familiarity with LLMOps tooling (LangSmith, LangChain, LangGraph). Understanding of model evaluation, validation, and production monitoring. Strong problem-solving skills ...

Engineer to design, build and operationalise advanced machine learning solutions that directly support UK national security objectives. This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation … including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards Transitioning validated experiments into production-ready ML services, collaborating closely with engineering teams on deployment and monitoring Building scalable ML pipelines using AWS services and modern experiment tracking frameworks Developing and integrating LLM-powered capabilities ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With Them Experience ...

Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic … Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … Them Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes ...

machine learning and deep learning models. Work on AI/ML projects including NLP, computer vision, recommendation systems, and generative AI. Perform data cleaning, feature engineering, and exploratory data analysis (EDA). Build and manage data pipelines and model training workflows. Deploy models into production and monitor performance. … Collaborate with Product, Engineering, and Business teams to translate business problems into AI solutions. Conduct model evaluation, A/B testing, and performance tuning. Document models, experiments, and technical processes. Required Skills & Qualifications Classic Machine learning (Regression, predictive Analysis, Classification, Clustering) Machine learning Model Optimisation Strong proficiency in Python ...

professionals on a mission to upgrade the insurance industry from the inside out. RESPONSIBILITIES The Full Stack Data Engineer is responsible for integrating data engineering, analytics, and data science to drive business intelligence and data-driven decision-making. They will design, implement, and optimize data pipelines, ETL processes … this role, as they work to deliver reliable, high performance data solutions aligned with elseco’s objectives. They will be joining the data engineering team to support the department in cultivating the enterprise data supply chain. Their activities will include preparing data for the creation of data products defined ...

clients. As a senior leader, you will interact frequently with customers, provide expert opinions, and contribute to HCL’s strategic vision. Key Responsibilities Technical & Engineering Leadership • Design and implement AI and cloud architectures, integrating GenAI technologies to enhance functionality and scalability. • Lead architectural discussions with clients, providing expert guidance … Skills & Experience • Deep knowledge of machine learning operations (MLOps) and experience in deploying, monitoring, and maintaining AI models in production environments. • Proficiency in data engineering for AI, including data preprocessing, feature engineering, and pipeline creation. • Expertise in AI model fine-tuning and evaluation, with a focus ...

Partner closely with data scientists to turn experimental models into well-engineered, production-ready systems Develop and maintain end-to-end ML pipelines, including feature engineering, training, evaluation, versioning, monitoring, and automated retraining Contribute to MLOps capabilities, including CI/CD pipelines, model registries, infrastructure automation, and containerised … regulatory requirements Advise business and product teams on opportunities for automation, predictive modelling, and GenAI enablement Contribute to reusable ML components, internal frameworks, and engineering best practices Stay up to date with emerging AI trends, tooling, and foundation models to inform strategic decision-making About You You will ...

annum Job Type: Full-time, Permanent About The Role We are looking for a talented and motivated Graduate AI Engineer to join our growing engineering team in Cambridge. This is an excellent opportunity for a recent graduate to work on real-world AI and machine learning problems, contributing … driven solutions while developing your technical and professional skills. Key Responsibilities Design, develop, and implement machine learning and AI models Assist in data preparation, feature engineering, and model evaluation Write clean, maintainable, and well-documented code Deploy and monitor models in production environments Collaborate with cross-functional teams ...

Scikit-learn. Programming skills in Python; familiarity with JavaScript is advantageous. Knowledge of cloud platforms like AWS and Azure. Experience with data preprocessing, feature engineering, and model evaluation. Excellent problem-solving, teamwork, and communication skills. Nice to have: Exposure to explainable AI (XAI), time-series forecasting, or NLP. ...

will you make an impact in this role? American Express Technologies is seeking a Senior Engineer with advanced skills in Generative AI and Data Engineering to join our Production Management tooling team. Our mission is to transform how critical platforms are supported by embedding AI-first solutions into event … develop Generative AI applications, including RAG pipelines, agentic workflows, and Model Context Protocol (MCP) integrations. Collaborate with data owners to build data pipelines, feature engineering processes, and context enrichment strategies that optimize AI-enabled solutions. Prototype and deliver production-ready tools leveraging LLMs, embeddings, vector databases, and orchestration ...

Learning models (e.g., classification, regression, clustering, deep learning) to solve complex business problems. Data Wrangling & Analysis: Perform comprehensive Exploratory Data Analysis ( EDA ), data cleaning, feature engineering, and transformation on large, complex, and sometimes unstructured datasets. Coding & Automation: Write production-quality, highly efficient, and scalable code primarily in Python ...

services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools (LangChain, LangSmith) Understanding of feature engineering and vector databases Strong grasp of CI/CD practices for ML deployment Why Join Us: Work with niche datasets and cutting-edge tech ...

ability to gut them and work with them past just surface-level functionality. Experience with the full model development lifecycle, from data preprocessing and feature engineering to model validation. Degree in Computer Science, Machine Learning, Computational Chemistry, or equivalent industry experience. Nice To Haves Prior experience in computational ...

models for user personalisation, including recommendation systems, ranking models, user segmentation, and content understanding, with a strong focus on TensorFlow-based development. Data Pipeline Engineering: Build and maintain scalable data pipelines to support feature engineering and model training across large structured and unstructured datasets, leveraging cloud‐native … relevance. Experimentation: Lead A/B testing and offline experimentation to evaluate model performance and guide ongoing improvement. Cross‐Functional Collaboration: Work closely with engineering, product, data, and research teams to ensure ML solutions align with product and business goals. Research & Innovation: Stay informed on advances in machine learning ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

Outside IR35 Clearance: Active SC Clearance required Email : henry.clay-davies@searchability.com Phone : 07719 065951 Overview We are seeking an experienced Data Science/Data Engineering Contractor to join a high-impact programme based in London, working on advanced data-driven and LLM-enabled platforms. This is an outside IR35 … data solutions Ensure data solutions meet security, performance, and maintainability standards expected in secure environments Required Skills & Experience Strong commercial experience in data engineering and/or data science roles Hands-on experience building data pipelines and AI-enabled workflows using LangChain and/or LangGraph Excellent Python development ...

cloud and on-prem data platforms , automation, and emerging AI-driven capabilities, and is specifically suited to candidates with strong, hands-on data engineering experience , particularly in building, operating, and optimising complex data pipelines, data models, and integration workflows at scale. Role Overview and Responsibilities As a Data & Automation … delivery processes using technologies such as Azure Data Factory, Databricks, SSIS, and SQL . Reducing manual interventions through automation and standardisation , including data preparation, feature engineering, and training-data pipelines. Preparing data models and datasets (DWH/Lakehouse) to support business intelligence, analytics, and operational reporting. Monitoring ...

Develop and support analytical and statistical models using Python 🛠 Work with real-world energy and environmental datasets, including data cleaning, validation, and feature engineering ☁️ Use AWS services to support data storage, processing, and analytics workflows 🗄 Query and manipulate structured datasets using SQL 📊 Build reports, dashboards, and visualisations that … tailored to experience, including bonus, pension, and generous annual leave ✅ What we’re looking for: 🎓 A degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field 💼 0–2 years of experience in data analysis or data science (graduate roles, internships, placements, or academic projects welcome) 🐍 Strong ...

things that go into production, and wants to learn from experienced engineers in a fast-moving environment. You’ll be part of a modern engineering function working on large-scale data and AI products, contributing to model development, data pipelines, and deployment workflows that power mission-critical platforms. … Build, train, and evaluate machine learning models using Python 📊 Work with large, complex datasets to support AI-driven products and insights 🧠 Assist with feature engineering, model experimentation, and performance optimisation ☁️ Contribute to data and ML pipelines in cloud-based environments 🗄 Work with structured and semi-structured data using ...