8 of 8 Remote Feature Engineering Jobs in England

monitoring processes Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes. Work closely with the data science team to integrate modelling approaches and techniques Key Skills and More ❯

data and AI strategy scales effectively, directly influencing the way millions of people engage with their products every day. The Opportunity This is a unique chance to combine data engineering with machine learning in a high-impact environment. You'll work closely with analysts, data engineers and stakeholders, ensuring models are reliable, scalable, and production-ready. Unlike many roles … work applied at scale, powering decision-making and user experiences for a vast audience. Your day-to-day will include: Building and maintaining end-to-end data pipelines and feature engineering workflows. Deploying and monitoring ML models in production using tools such as MLflow, Vertex AI, or Azure ML. Driving best practices in MLOps, including CI/CD … gym access. Access to wellbeing support services and employee assistance programmes. Clear career progression and opportunities to work with cutting-edge tech. Skills and Experience Degree in Computer Science, Engineering, Mathematics, or a related field. Proven experience in data or ML engineering. Strong knowledge of Python and SQL. Hands-on experience with cloud platforms (GCP or Azure) and Databricks. More ❯

Key Skills Proficiency in Python and/or R for developing machine learning models. Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms like AWS, GCP, or Azure for deploying ML solutions. Knowledge of version control systems (e.g., Git) and CI/ More ❯

and product managers, to deliver robust AI solutions. Key Skills Proficiency in Python, TensorFlow, or PyTorch Experience with machine learning algorithms and frameworks Strong understanding of data pre-processing, feature engineering, and model evaluation Familiarity with cloud services (AWS, GCP, Azure) and their AI/ML offerings Knowledge of natural language processing (NLP) and computer vision is a More ❯

the lead on projects that improve the core discovery experience-such as personalisation, relevance ranking, and multi-modal retrieval-as well as conduct deep investigations into user behaviour and feature performance. You'll be working across the full research and experimentation lifecycle: from framing the problem and exploring the data, to prototyping models, running offline evaluations, and validating ideas … technical direction Qualifications 5+ years of experience in applied data science, preferably in search, recommendations or user modelling Strong Python and SQL skills, with deep experience in data exploration, feature engineering and model evaluation Proven experience applying and comparing models for structured prediction, ranking, retrieval or recommendation Strong understanding of offline evaluation techniques and trade-offs in information … retrieval and recommender systems Ability to communicate clearly across disciplines and seniority levels-including product, design and engineering Experience planning and delivering projects end-to-end, from problem definition to experimentation and rollout Familiarity with AB testing design and analysis in online product settings Bonus: experience working with embeddings (e.g. image, text, product), vector search, LLMs or hybrid models More ❯

in this journey, working on cutting-edge projects that enhance our digital presence and improve customer engagement. As a Principal AI Engineer, you will be part of the Technology Engineering team within CIO, leading the design, development, and deployment of advanced AI and machine learning solutions that drive innovation, efficiency, and strategic value across the organisation. You will collaborate … closely with cross-functional teams, including Data Science, Engineering, Product, and Business stakeholders, to understand complex business challenges and identify opportunities where AI can deliver measurable impact. You will lead the end-to-end lifecycle of AI initiatives - from problem framing and data exploration to model development, deployment, and monitoring - ensuring solutions are scalable, ethical, and aligned with enterprise … goals. Skills we would love you to have: Extensive experience in AI/ML engineering, data science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML libraries (e.g. Semantic Kernel, Langchain and Agentic frameworks). Experience deploying models into production using APIs, containers More ❯

build out new analytics products for claims and underwriting Execute data analysis and exploratory analysis (project design, processing of and cleaning of data, merging/joining disparate data sources, feature engineering, performing analyses and communicating results). Produce models using a variety of algorithms (GLM, GBM, Random Forest, Neural Networks etc.) and assess the relative strength of each More ❯

to drive innovation into the product development process. You will interpret your clients objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯