14 of 14 Remote/Hybrid Feature Engineering Jobs in London

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. Leads the definition and execution of AI/ML engineering direction across one or more squads, ensuring alignment with ...

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 ...

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 ...

taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization … inference, experimentation, monitoring, and continuous improvement. Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems. Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical ...

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 ...

queries and manage remediation actions and findings Your skills and experience Advanced degree (Master’s or PhD) in a quantitative discipline (e.g., Mathematics, Physics, Engineering, Computer Science) 7+ years’ experience developing analytical or machine learning models in financial services (ideally Anti-Financial Crime/Screening) Experience building Natural Language … Processing (NLP)/Machine Learning (ML)/Artificial Intelligence (AI) pipelines, including feature engineering, model training, evaluation and monitoring Experience designing evaluation frameworks for LLM use cases (e.g., human-in-the-loop, calibration, guardrails, auditability) Experience with hyperparameter tuning at scale and experimentation frameworks Strong technical experience with ...

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. … with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across ...

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. … with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across ...

teams to align architecture with business objectives. Provide technical leadership and governance across AI work streams and delivery teams Drive best practice in AI engineering, model management, and data science operations Evaluate and select appropriate AI frameworks, tools, and cloud services to meet enterprise requirements Support the integration … systems Skills and Experience Proven experience delivering AI solutions at enterprise scale in production environments Strong background in Generative AI — including LLMs, prompt engineering, and model fine-tuning Hands-on experience with Hugging Face (model hub, Transformers, Inference API) Experience with AWS AI services (SageMaker, Bedrock, Rekognition, Comprehend ...

advanced ranking models for Depop’s entire app, covering personalised recommendations, search results and other surfaces. Collaborate closely with cross-functional partners (product, engineering, data) to define problems, translate them into scalable solutions, and deliver measurable business outcomes. Lead the end-to-end lifecycle of ML projects: from ideation … data acquisition, feature engineering, training, and evaluation to deployment and ongoing iteration. Drive innovation in ranking by researching and integrating emerging ML techniques, frameworks, and tooling, while contributing technical expertise to long-term product and data strategy. Mentor, coach, and set technical direction within the Ranking ML team ...

models (e.g., clustering, regression, predictive analytics) with ability to take problems from framing through to deployment-ready outputs Must be strong in data exploration, feature engineering, model evaluation, and communicating insights clearly to non-technical stakeholders ideally within demand-led public services (predictive demand, prevention, triage/segmentation ...

real-time capability Strong understanding of how to assess and enable data readiness for AI use cases, including data availability, data quality and feature engineering considerations Experience analysing decision-making workflows, identifying where data should better inform operational and strategic decisions Ability to establish and promote canonical data ...

will be responsible for designing, building, and governing predictive models that support data-driven products and strategic decision-making. You will work closely with engineering and product teams to transform raw data into robust, auditable, and commercially valuable solutions. Skills & Experience Technical Expertise Strong proficiency in Python (Pandas, NumPy … Snowflake or similar cloud-based data warehouse platforms. Experience using Git and reproducible development practices. Strong understanding of data pipelines, data quality, and analytics engineering principles. Credit Modelling & Predictive Analytics Proven experience conducting rigorous exploratory data analysis and feature engineering. Experience building predictive models in regulated financial services ...