1 to 25 of 30 Remote/Hybrid Feature Engineering Jobs in London

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 ...

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 ...

ontologies, 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, question … preprocessing, 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 audiences.RequirementsExperience ...

world.As a Principal Data Engineer you will set the medium to long term technical direction for our data infrastructure. You will partner with Engineering, Data Science, Product and SRE leadership on cross-tribe initiatives, coach engineers at every level, and tackle the data problems that no single team … solve alone. You will also represent ComplyAdvantage at engineering and industry events.Your impact will shape the data foundations on which ComplyAdvantage's AI, screening and monitoring products are built. Your work will directly affect how quickly and accurately our customers can detect money laundering, terrorist financing, sanctions evasion ...

bridge the gap between machine learning, data science, and engineering. What you’ll do Shape the architecture of data products built for: analytics forecasting feature engineering customer behavior insights integration of new data sources Data Transformation & Governance Lead best practices in: data modelling performance optimization governance consistent reliable … Explore open-source tools Engage with the broader tech community Help keep Prima at the cutting edge What we’re looking for Software & Data Engineering Strong expertise in Python Passion for writing: clean reliable production-grade code Distributed Data Processing Experience building and operating: batch processing systems distributed data ...

with new estimators, models and features to boost payment performance across our portfolio of merchants. You will work closely with Data Scientists, Product and Engineering to enhance our core offering, protect customer lifetime value through network intelligence, and ensure safe model launches through robust observability.Key ResponsibilitiesContribute to the research … with other Data Scientists and engineers to productionise ML features, models and evolve our evaluation and monitoring frameworks.Write high-quality, interpretable Python code for feature engineering and model training, contributing directly to our core products.Communicate hypotheses, evaluation results, and monitoring dashboards clearly to both technical and non-technical ...

experimenting with new estimators, models, and features to boost payment performance across our merchants portfolio. You will work closely with Data Scientists, Product, and Engineering to enhance our core offering, protect customer lifetime value through network intelligence, and ensure safe model launches through robust observability. Key Responsibilities Contribute … other Data Scientists and engineers to productionise ML features, models, and evolve our evaluation and monitoring frameworks. Write high‐quality, interpretable Python code for feature engineering and model training, contributing directly to our core products. Communicate hypotheses, evaluation results, and monitoring dashboards clearly to both technical ...

before production deployment. Develop robust ML pipelines using AWS services and MLOps tooling. Implement experiment tracking, model versioning, monitoring, and reproducibility best practices. Build feature engineering pipelines and contribute to feature store development. Monitor production models, optimise performance, and drive continuous improvements. Apply Responsible AI principles, including … technical concepts to both technical and non-technical stakeholders. Desirable Experience AI agents and agentic workflows. Vector databases such as Pinecone, Weaviate, or pgvector. Feature stores including Feast or AWS Feature Store. Docker, Kubernetes, or Amazon ECS. Infrastructure as Code using Terraform or CloudFormation. Big data processing technologies ...

seeking to hire talented AI Engineers(s) within our AI Scaling and Transformation team, which is a centre of excellence in Deloitte's Engineering, AI & Data service offering.You will work alongside clients, third parties, and Deloitte teams from across the Firm, supporting a wide range of international and market … looking for candidates who are able to demonstrate skills and experience in some of the following:EDUCATION & EXPERIENCEDegree or equivalent in Computer Science, Data Engineering, Mathematics, Artificial Intelligence, or a related discipline; advanced degrees are welcome but not essentialStrong technical background, with hands-on experience in developing and deploying ...

variety of interesting, international, and world-leading clients on exciting next generation technology-enabled projects. We are looking for candidates with AI/ML Engineering expertise to join us, working in fast-paced teams with talented colleagues across the UK and Deloitte’s wider delivery network.We encourage consideration … with some flexibilities, please do discuss it with us.Your roleAs a practitioner in AI & Data, you are responsible for delivering AI/ML Engineering on client projects. You are encouraged to devise innovative solutions to help our clients address their biggest data challenges including developing modern analytics platforms.AI/ ...

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 as gradient … environments.Graph & 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 proficiency ...

Date published 31-Jul-2026 Req # 23230 Job description Connect to your IndustryDeloitte’s AI for Sustainability and Infrastructure team sits within our Engineering, AI & Data offering area and is purpose built to help our client’s lead and win through the transition to a low‐carbon, digitally … strategies aligned with their energy transition and operational efficiency goals.Lead the design, development, and implementation of advanced AI pipelines, encompassing data acquisition, preprocessing, feature engineering, model development, evaluation, and secure deployment at scale.Oversee the development and operationalisation of state-of-the-art AI models, including large language models ...

seeking to hire experienced Lead GenAI System Architect(s) in the AI Institute, which is a centre of excellence in Deloitte's Engineering, AI & Data service offering.You will be working with clients and other third parties, as well as Deloitte teams from across the Firm. You will have … deliver transformative AI and Generative AI strategies aligned with business goals.Lead the design, development, and implementation of advanced AI pipelines, encompassing data acquisition, preprocessing, feature engineering, model development, evaluation, and secure deployment at scale.Oversee the development and operationalisation of state-of-the-art AI models, including large language ...

iterating on models before production deployment.Develop robust ML pipelines using AWS services and MLOps tooling.Implement experiment tracking, model versioning, monitoring, and reproducibility best practices.Build feature engineering pipelines and contribute to feature store development.Monitor production models, optimise performance, and drive continuous improvements.Apply Responsible AI principles, including explainability, governance … both technical and non-technical stakeholders.Desirable ExperienceAI agents and agentic workflows.Vector databases such as Pinecone, Weaviate, or pgvector.Feature stores including Feast or AWS Feature Store.Docker, Kubernetes, or Amazon ECS.Infrastructure as Code using Terraform or CloudFormation.Big data processing technologies such as Spark or Dask.Experience working within regulated or highly secure ...

product teams, AI agents, and external customers depend on for clean, reliable data.This Senior Manager role spans both teams. It is a data and engineering leadership role with a strong product backbone, designed for a builder-leader. You need to understand what good AI feature engineering looks … like, what it takes to build end-to-end data products, data engineering best practice, and how to build and lead teams that do both well. You will stay close enough to the work to shape technical direction, unblock delivery, and raise the quality bar across both teams.Who ...

your opportunity We are seeking to hire experienced ML Engineers within our AI Scaling and Transformation team, a centre of excellence in Deloitte’s Engineering, AI & Data service offering.You will work alongside clients, third parties and Deloitte teams across the Firm, supporting Security & Justice organisations to design, build … machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps and production ML practices, including CI/CD, model versioning, automated testing, retraining ...

understand business requirements and translate them into robust AI solutions.Design, develop, and implement end-to-end AI pipelines, including data acquisition, pre-processing, feature engineering, model training, evaluation, and deployment.Build and maintain scalable and efficient AI models using machine learning, deep learning, and other advanced analytics techniques.Stay abreast … want to help solve some of the biggest tech and transformational challenges around, join us. Together, we’ll make an impact that matters. Engineering, AI and DataWe lead transformation at the heart of our clients; re-engineering the core of our clients’ organisations, helping to unleash growth ...

using distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems.Mentor junior team members and utilise model explainability methods to drive feature performance improvements.About You5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale business problems.Deep understanding of frequentist … Bayesian statistics, plus supervised and unsupervised modelling techniques.Proven experience modelling complex interactions (e.g., cluster or network effects).Expertise in model explainability to tune feature engineering and understand feature interactions.Ability to write high-quality, production-grade Python code and collaborate effectively with non-technical stakeholders.Proficient in leveraging LLMs ...

distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems. Mentor junior team members and utilise model explainability methods to drive feature performance improvements. About You 5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale business problems. Deep … statistics, plus supervised and unsupervised modelling techniques. Proven experience modelling complex interactions (e.g., cluster or network effects). Expertise in model explainability to tune feature engineering and understand feature interactions. Ability to write high-quality, production-grade Python code and collaborate effectively with non-technical stakeholders. Proficient ...

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 ...

platform design. Ensure architectures meet security, privacy, and regulatory requirements, including GDPR and data residency considerations. Review solution designs, provide architectural assurance, and support engineering teams through design authority and peer review. Design data architectures that enable AI adoption — ensuring data is discoverable, well-governed, and AI-ready … machine learning, GenAI, and agentic use cases across the business. Partner with AI/ML teams to define patterns for feature engineering, model data pipelines, vector search, and safe exposure of enterprise data to AI systems. Evaluate emerging technologies and make pragmatic build/buy/adopt recommendations ...

learning models focused on user personalisation, including recommendation engines, ranking algorithms, user segmentation and content analysis. Construct and maintain robust, scalable data pipelines for feature engineering and model training, handling both structured and unstructured large‐scale datasets. Deploy and supervise ML models in production, ensuring high availability, optimal ...

rankers.Entity/relationship extraction/resolutionKnowledge Graphs; building and inference, graphRAGRecommendation systems and ranking: personalisation, learning-to-rank, feed ranking, user modelling, etc.Tabular ML: feature engineering, structured data modelling (GBDTs, etc.)Statistical & Predictive Modelling: supervised ML, anomaly detection, temporal modelling, etc.Deep understanding of the GenAI landscape and agentic ...

Strong Python and Pandas. Advanced SQL. Experience working with Azure Data Lake or similar cloud data platforms. Experience working with very large datasets. Strong feature engineering experience. Experience improving production classification models. Excellent understanding of F1 Score, Precision, Recall and model evaluation. Experience working with highly imbalanced datasets. ...

come beyond. Our UK customers can also save, invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments … scales into new marketsshaping how advanced ML and AI can create real value in BorrowingYou’ll partner closely with leaders across Credit Strategy, Product, Engineering, Model Validation, Data, and Platform, and influence decisions that shape both business performance and the long-term architecture of credit decisioning at Monzo. What ...