12 of 12 Remote/Hybrid Feature Engineering Jobs in London

applications, integrating AI models into business systems, and supporting the full AI development lifecycle. The ideal candidate is passionate about modern AI technologies, software engineering best practices, and delivering reliable AI solutions at scale. Key Responsibilities AI Application Development Design, build, and maintain AI-powered applications and services. Develop … Retrieval-Augmented Generation (RAG) systems and AI agents. Integrate foundation models and APIs into enterprise applications. Create reusable AI components and frameworks. Machine Learning Engineering Train, fine-tune, evaluate, and deploy ML models. Develop feature engineering and model evaluation pipelines. Implement model monitoring and performance tracking. Optimize ...

Experience designing and analysing A/B tests, defining success metrics, understanding selection bias, and evaluating ranking systems using both online and offline methodologies. Feature Engineering & Applied Machine Learning : Strong background in feature engineering, tabular machine learning, calibrated scoring systems, and production use of models such … Entity‐Aware Ranking : Ability to incorporate relationships between companies, sponsors, lenders, law firms, instruments, documents, and events into ranking and recommendation decisions. Production ML Engineering : Experience building feature pipelines, online and batch inference systems, low‐latency ranking services, experimentation platforms, and monitoring for production machine learning systems. Strong ...

collaboratively across a fast-moving technology company, turningcutting-edgeresearch into practical, scalable solutions.This role reportsto the AppliedAILead. Responsibilities Lead data identification, cleaning, enrichment, preprocessing,feature engineering,andexploratoryanalysis to ensure fitness for AI workflows and to inform modelling and business decisions. Build, tune, andoptimisemachine learning, deep learning, and generative … models,leveragingboth established andcutting-edgetechniques. Designand buildLLM-powered systems— RAG pipelines, prompt and context engineering, fine-tuning, structured outputs, function calling, context-window management,and secure model integration;selectingappropriately between standard and reasoning (test-time-compute) models, balancing capability against latency and cost. Designand buildagentic AI systems— tool-calling ...

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 ...

concept into production environments Develop scalable ML pipelines using AWS cloud technologies Implement MLOps and LLMOps best practices for deployment, monitoring and governance Support feature engineering, model optimisation and performance monitoring Apply responsible AI principles, including model explainability and fairness Present findings and recommendations to technical … tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering and RAG architectures Experience with LLMOps tools such as LangChain, LangSmith or LangGraph Strong understanding of model monitoring, validation and governance Excellent communication ...

value creation initiatives to be backed by reliable, real-time data. When companies partner with JMAN, we combine our data science and data engineering expertise with our deep commercial understanding to deliver tangible, high-value outcomes at pace. Founded in 2010, JMAN has a global footprint with offices … Data Science or applied machine learning, ideally in consulting, high‐growth, or commercial environments. Strong applied machine learning expertise, including: Model selection and development Feature engineering Evaluation and validation Deployment into production environments Demonstrated experience taking models beyond experimentation into operational, business‐critical systems. Strong background in statistics ...

Purpose of the Role To drive technical excellence and innovation by leading the design and implementation of robust software solutions, providing mentorship to engineering teams, fostering cross‐functional collaboration, and contributing to strategic planning to ensure the delivery of high‐quality solutions aligned with business objectives. Accountabilities Provision … guidance and expertise to engineering teams to ensure alignment with best practices and foster a culture of technical excellence. Contribution to strategic planning by aligning technical decisions with business goals, anticipating future technology trends, and providing insights to optimise product roadmaps. Design and implementation of complex, scalable, and maintainable ...

solutions. In this key role you’ll turn fraud, credit risk, financial crime, compliance and regulatory needs into clear technology requirements, providing mentorship to engineering teams, fostering cross‐functional collaboration, and contributing to strategic planning to ensure the delivery of high‐quality solutions aligned with business objectives. … customer onboarding, and real‐time decision management Some other highly valued skills may include: Experience operationalising AI/ML solutions including model lifecycle management, feature engineering, vector databases, RAG architectures, AI governance and production‐scale MLOps Experience building modern data platforms incorporating data mesh/Lakehouse architectures, real ...

complex real-world environment. You'll be involved in: ·Developing machine learning models to improve forecasting and operational planning ·Applying time-series analysis and feature engineering techniques across large datasets ·Building and improving discrete event simulation models to test different scenarios ·Identifying trends, patterns and potential operational constraints … Python experience beneficial) ·SQL and working with large datasets ·Ability to explain technical findings clearly to different audiences A background within transport, logistics, aviation, engineering, manufacturing, supply chain or similar operational environments would be highly advantageous. This would suit a Data Scientist who enjoys modelling how things work, testing ...

domains involving high-frequency or large-scale time-series data. You will focus on developing alpha signal generation pipelines from data ingestion and feature engineering to model training and deployment - in collaboration with our trading and infrastructure teams. Responsibilities Develop ML-based alpha generation models using high-frequency … order book and market microstructure data. Design and maintain data pipelines, preprocessing, and feature extraction workflows tailored to streaming tick data. Research and implement advanced deep learning architectures for short-horizon forecasting and signal extraction. Collaborate with quant researchers and developers to integrate models into live trading environments. Optimise ...

procurement. We are seeking an experienced data scientist to develop forecast models for energy, metals, and other inputs, owning the full modelling lifecycle from feature engineering to deployment. You will integrate diverse data sources and translate probabilistic forecasts into procurement decisions, collaborating closely with our engineering team ...