21 of 21 Remote/Hybrid Feature Engineering Jobs in the UK

realise the full potential of an AI enabled future. Key Responsibilities Build and ship production ready AI/ML features-from data ingestion and feature engineering to model training, evaluation, and deployment Develop LLM/GenAI solutions (prompt engineering, tool use, guardrails) and RAG pipelines (chunking, embeddings … efficient memory/latency tuning Build and maintain MLOps/LLMOps workflows-CI/CD for models and prompts, model registry/versioning, feature stores, and automated promotion across environments Instrument observability for data, models, and prompts (telemetry, metrics, traces, dashboards, alerts); implement A/B tests and online ...

driven decision making across complex digital transformation programmes. Working with modern data platforms, high-quality datasets, and advanced AI frameworks, you will collaborate with engineering, product, and analytics teams to build models that are accurate, explainable, and scalable. The role empowers you to shape end-to-end analytical ecosystems … Collaborate with data engineers, analysts, product managers, and domain experts to translate business requirements into modelling tasks * Build end-to-end ML pipelines, including feature engineering, preprocessing, and deployment-ready outputs * Apply advanced techniques such as NLP, time series forecasting, anomaly detection, optimisation, or LLM/GenAI methods ...

complex digital transformation programmes. With access to modern data platforms, high quality datasets, and advanced statistical and AI frameworks, you will work closely with engineering, product, and analytics teams to build solutions that are accurate, explainable, and scalable. This role empowers you to shape end to end analytical ecosystems … data engineers, analysts, product managers, and domain experts to translate business requirements into well defined modelling tasks Build end to end ML pipelines-from feature engineering and preprocessing to deployment ready model outputs Apply advanced techniques such as NLP, time series forecasting, anomaly detection, optimisation, or LLM/ ...

complex digital transformation programmes. With access to modern data platforms, high-quality datasets, and advanced statistical and AI frameworks, you will work closely with engineering, product, and analytics teams to build solutions that are accurate, explainable, and scalable. This role empowers you to shape end-to-end analytical ecosystemsaccelerating … with data engineers, analysts, product managers, and domain experts to translate business requirements into well-defined modelling tasks. Build end-to-end ML pipelinesfrom feature engineering and preprocessing to deployment-ready model outputs. Apply advanced techniques such as NLP, time-series forecasting, anomaly detection, optimisation, or LLM/ ...

making across complex digital transformation programmes. With access to cutting edge AI frameworks, high performance computing environments, and modern data platforms, you will guide engineering and data science teams in building secure, scalable, and ethical AI systems. This role empowers you to shape end to end AI ecosystems-accelerating … more intelligent, AI enabled future. Key Responsibilities Define the enterprise AI architecture vision and reference patterns; align them to business goals, risk posture, and engineering standards across cloud and hybrid environments Design secure, scalable AI solutions covering data ingestion, feature engineering, model training, inference, and continuous feedback ...

making across complex digital transformation programmes. With access to cutting-edge AI frameworks, high-performance computing environments, and modern data platforms, you will guide engineering and data science teams in building secure, scalable, and ethical AI systems. This role empowers you to shape end-to-end AI ecosystemsaccelerating delivery … more intelligent, AI-enabled future. Your responsibilities: Define the enterprise AI architecture vision and reference patterns; align them to business goals, risk posture, and engineering standards across cloud and hybrid environments. Design secure, scalable AI solutions covering data ingestion, feature engineering, model training, inference, and continuous feedback ...

based 3 days per week and comes with a solid Bonus and some fantastic benefits. You’ll be surrounded by Analytics, Data Science and Engineering Colleagues in this meritocratic and highly collaborative team. The Role: You’ll be the most senior hands-on technical contributor within the team … will aid in the design and delivery of complex engineering workloads, provide mentorship to the wider team, and help set and uphold engineering standards across our Databricks platform. The ideal candidate combines deep technical expertise with a natural inclination to bring others along with them. ...

accessible for 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.Drive … management across business, IT and compliance teams. Excellent communication, collaboration and influencing skills at all levels of an organisation. Experience leading data architecture and engineering teams in an enterprise environment. Ability to define and implement a data strategy aligned with business objectives. Proven track record of delivering enterprise-scale ...

Join our dynamic team and be part of building a greener, cleaner future! About the Role : The Technical Delivery Lead is a hands-on engineering role responsible for designing, building, and optimising solutions across Microsoft Fabric, Azure Integration Services (Logic Apps & Function Apps), Power Platform, and Power BI. This … role brings together technical engineering and strategic influence, contributing to technology direction, security standards, and architectural best practices in alignment with the Head of IT. The ideal candidate is a highly capable technical lead with strong data engineering and security awareness, who enjoys solving complex problems and delivering ...

Experience working within Azure data environments , ideally: Azure Machine Learning Databricks Microsoft Fabric/Synapse Experience deploying models into production environments Strong understanding of: feature engineering model evaluation MLOps principles Consulting/Soft Skills (Critical) Proven ability to work directly with clients and stakeholders Strong communication and presentation ...

including customers, sales teams and product teams Help customers develop an understanding of how behavioural AI models drive business outcomes Collaborate with product and engineering teams to identify new opportunities for data science innovation Contribute to the internal data science community and share best practices Skills & Experience Essential Strong … data science solutions that drive measurable business outcomes Experience building and evaluating machine learning models (e.g. clustering, NLP, deep learning) Experience with data exploration, feature engineering and model evaluation Familiarity with modern AI tooling and frameworks (e.g. agentic AI, MCP servers or similar AI infrastructure) Ability to work ...

investors and data-driven organisations. With data and AI at the core of their product, they are scaling quickly and investing heavily in their engineering and AI capabilities. You will join a collaborative, fully remote team that values transparency, curiosity and speed of execution. The Role You will … small, focused AI team and work closely with engineering to design, build and productionise new AI features across the platform. Key responsibilities include: Designing, training and deploying AI and ML models on complex, large-scale data. Building GenAI solutions using techniques such as RAG and frameworks like LangChain ...

long-term operational ownership. As our new Data Scientist (Machine Learning) you will be responsible for: Build predictive, forecasting and anomaly-detection models Perform feature engineering & validation using Python/PySpark Work in Fabric Notebooks, Delta Lakehouse, and AutoML Embed models into production pipelines with our Data Engineering ...

long-term operational ownership. As our new Data Scientist (Machine Learning) you will be responsible for: Build predictive, forecasting and anomaly-detection models Perform feature engineering & validation using Python/PySpark Work in Fabric Notebooks, Delta Lakehouse, and AutoML Embed models into production pipelines with our Data Engineering ...

ownership and production-grade model deployment. The Role As Senior Data Scientist, you will: Own end-to-end ML solutions -from problem framing and feature engineering to deployment, monitoring, and governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models … using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift, and retraining Drive clear documentation, traceability, and governance appropriate for a regulated environment This role requires someone ...

will: Lead and develop a growing Data Science team, setting standards and delivery cadence Own end-to-end ML solutions -from problem framing and feature engineering to deployment, monitoring, and governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models … using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift, and retraining Drive clear documentation, traceability, and governance appropriate for a regulated environment This role requires someone ...

based MMM notebooks to incorporate additional media channels Prepare and validate input data from multiple sources prior to modelling Perform data cleaning, transformation, and feature engineering Run, calibrate, and sense-check MMM model outputs Support model validation and quality checks to ensure outputs are robust and usable Document ...

skills with experience querying large scale relational databases such as Azure SQL or PostgreSQL Experience working with high volume or time based data, including feature engineering Experience with simulation, discrete event simulation, or operations research techniques is highly desirable Ability to communicate complex analysis clearly to non-technical ...

Markets domains (counterparties, instruments, legal entities, regulatory taxonomies). Implement graph-RAG patterns for multi-hop reasoning and relationship-aware retrieval. 3. Vector Database Engineering — Architect and optimise the vector storage layer — embedding model selection, chunking strategies (semantic, hierarchical, sliding window), index tuning (HNSW, IVF-PQ), metadata filtering, hybrid … data governance, Delta Lake for reliable storage, Databricks Vector Search for managed embeddings, and Spark/SQL for large-scale data processing and feature engineering. 6. Query Routing & Orchestration — Implement intelligent query routing agents that decompose complex user questions into sub-queries, determine the optimal retrieval source (vector, graph ...

champion their adoption across teams. Responsibilities •Act as a data strategist to identify, integrate, and leverage new data sources through product capabilities. •Collaborate with engineering teams to build, test, and deploy scalable data products and predictive models. •Execute analytical experiments to address challenges across multiple business domains. •Mine … science or a related field. •Proven expertise in data mining, statistical modelling, and machine learning techniques. •Advanced experience in pattern recognition, predictive modelling, and feature engineering. •Proficiency in Python and SQL, and a solid grasp of software engineering best practices. •Strong understanding of data structures, model evaluation ...

PyTorch, TensorFlow, or scikit-learn. LLM Experience: Proven experience working with large language models (e.g. GPT, Claude, Gemini) in production environments, including prompt engineering, evaluation, and safety considerations. Strong Engineering Skills: Proficiency in Python and TypeScript, with experience building APIs, microservices, and cloud-native applications. Modern AI Tooling … including CI/CD, model versioning, observability, and retraining pipelines. Data Fluency: Skilled in working with structured and unstructured data, including preprocessing and feature engineering. User-Centred Mindset: Ability to translate complex AI capabilities into intuitive and seamless product experiences. Collaborative Approach: Thrives in cross-functional, creative teams ...