26 to 50 of 148 Feature Engineering Jobs in London

experienced Machine Learning Engineer with SC Clearance. Key Responsibilities: Develop and optimise ML models for personalisation and recommendations Build scalable data pipelines and feature engineering workflows Deploy, monitor and optimise ML models in production Lead A/B testing and experimentation to improve model performance Collaborate with cross … solutions Evaluate and apply emerging ML and deep learning techniques Key Skills Required: Machine Learning/Deep Learning Recommendation & Personalisation Systems Data Pipelines & Feature Engineering MLOps & Production Deployment A/B Testing & Experimentation Python/ML Frameworks Large-scale Structured & Unstructured Data To be Considered: Please either apply ...

experienced Machine Learning Engineer with SC Clearance. Key Responsibilities: Develop and optimise ML models for personalisation and recommendations Build scalable data pipelines and feature engineering workflows Deploy, monitor and optimise ML models in production Lead A/B testing and experimentation to improve model performance Collaborate with cross … solutions Evaluate and apply emerging ML and deep learning techniques Key Skills Required: Machine Learning/Deep Learning Recommendation & Personalisation Systems Data Pipelines & Feature Engineering MLOps & Production Deployment A/B Testing & Experimentation Python/ML Frameworks Large-scale Structured & Unstructured Data To be Considered: Please either apply ...

will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. Job Overview The Engineering AI Enterprise Architect is a senior AI technical authority responsible for the safe, consistent and scalable use of AI across a global engineering organisation. The role owns the Engineering AI solution design framework, including the architecture principles, reusable patterns, technical standards and production expectations used by business units to design AI models, agents, workflows and solution concepts. It helps identify common AI capabilities, reduce duplication and ensure local solutions are positioned ...

Things. Reply’s services include Consulting, System Integration, and Digital Services. Role Overview: We are looking for a mid/senior-level AI Testing & Engineering Specialist with strong Python expertise and solid experience in AI, Data Engineering, or Test Automation. The role is focused on building and evolving … generative AI agents, including evaluation pipelines, synthetic data generation, observability layers, and quality metrics for LLM-based systems. You will work across AI engineering, data pipelines, and quality automation, contributing both to architecture design and hands‐on implementation of scalable testing and evaluation systems. This role is suited ...

emerging AI technologies and recommend practical applications across the organisation. Data Science & Analytics Perform advanced statistical analysis and modelling across large‐scale operational and engineering datasets. Develop feature engineering, experimentation and model evaluation frameworks. Create insights and recommendations that drive decision making for senior stakeholders. Build … maintain reproducible data science workflows and pipelines. Product Delivery Partner with engineering and product teams to transition solutions from proof‐of‐concept into production. Define success metrics and measurement frameworks for AI products. Support model monitoring, governance and continuous improvement activities. Contribute to AI product roadmaps and prioritisation discussions. ...

technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards. You will contribute … compliance framework. This is a highly hands‐on, highly technical, principal‐level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps. Key ResponsibilitiesTechnical Leadership & ArchitectureDefine the end‐to‐end ML architecture for the matching platform, including data pipelines, model training workflows, inference ...

Solirius Reply, part of the Reply Group, is a technology consultancy and digital transformation partner that helps organisations solve complex challenges through strategy, design, engineering, and delivery. We work closely with our clients to deliver secure, accessible, user-focused services that evolve with their needs. By combining deep technical … Ministry of Housing, Communities and Local Government, UEFA, International Olympic Committee, and Mercedes-Benz. Our services span the full digital delivery lifecycle, including architecture, engineering, delivery management, user-centred design, business analysis, data, DevOps, and AI. We operate as a collaborative and inclusive organisation that empowers our people ...

seeking an AI Data Scientist to help build intelligent, data-driven products. You will design, develop, and deploy machine learning models, working across data engineering and analytics to solve complex business problems. Youll collaborate with product, engineering, and business teams to transform data into actionable insights and high … models (e.g., predictive models, NLP, computer vision, recommender systems). Explore, cleanse, and transform large structured and unstructured datasets Conduct statistical analysis, experiment design, feature engineering, and model evaluation. Build scalable data pipelines and automate model training and inference processes. Collaborate with engineering teams to integrate models ...

technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards. You will contribute … compliance framework. This is a highly hands‐on, highly technical, principal‐level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps. Key Responsibilities Technical Leadership & Architecture Define the end‐to‐end ML architecture for the matching platform, including data pipelines, model training ...

value-based decisioning logic — incorporating CLV and long-term customer value into prioritisation, not just short-term conversion Measurement frameworks and optimisation Define feature engineering requirements — knowing which signals, triggers, and contextual features drive predictive power in decisioning Architect real-time decisioning solutions integrating with … SNGCR01 Required — Technical Skills Advanced Python — writing clean, production-grade code, not just scripts (OOP, async, packaging, testing) Generative AI & LLM development — prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning — model development, training ...

will work at the intersection of Computer Science, Mathematics, and Statistics — building high-performance tools that enable world-class research while maintaining a high engineering standard. Responsibilities Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies Develop and maintain complex data … pipelines, including data ingestion, feature engineering, validation, and quality monitoring Translate research prototypes and novel ideas into performant, well-tested, production-ready code Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle Supervise, understand, and remediate subtle data quality issues across both research ...

other project and practice data, translating technical capability into tools and workflows that practitioners can use. This is a digitally transformative, hands‐on engineering role focused on building, deploying, maintaining, and optimizing machine learning systems and data pipelines, working with large‐scale datasets to power production‐ready intelligent systems … internal applications, dashboards, and Gensler IP. Own the production ML lifecycle on Azure — deployment, monitoring, versioning, retraining, rollback, and incident response — including model registries, feature stores, evaluation frameworks, and benchmarking. Implement CI/CD, testing, reproducibility, and deployment standards for model and data workflows. Extend and mature cloud data ...

will work at the intersection of Computer Science, Mathematics, and Statistics — building high-performance tools that enable world-class research while maintaining a high engineering standard. ResponsibilitiesPartner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategiesDevelop and maintain complex data pipelines, including … data ingestion, feature engineering, validation, and quality monitoringTranslate research prototypes and novel ideas into performant, well-tested, production-ready codeBuild extensible tools and frameworks that accelerate the model development and experimentation lifecycleSupervise, understand, and remediate subtle data quality issues across both research and production environmentsProactively lead projects from ...

Analysis: Develop, train and evaluate models using statistical and machine learning techniques, with a focus on probabilistic approaches. Contribute across the modelling lifecycle from feature engineering and training through to validation and deployment. Data Work: Query, clean and explore datasets using Python and SQL to surface patterns … statistical techniques. Comfortable working with probabilistic models, uncertainty estimation and Bayesian inference. Model Development: Understanding of the full model training pipeline, including data preparation, feature selection, model selection and model validation. Experience: Hands-on experience building and evaluating models in a data science or quantitative context. Python & SQL: Comfortable ...

with high autonomy, owning your projects from the initial exploratory analysis through to production deployment. In this role, you will work closely with Product, Engineering, and Business stakeholders to deliver solutions that optimize our operations, refine our marketing efforts, and enhance the customer experience. You will not only build … powerful models but also help uphold the engineering rigor and standards of our data team. You Will: Build from Scratch: Thrive in a 0-to-1 environment. You are comfortable rolling up your sleeves to write complex SQL, engineer your own features, and deploy baseline models (heuristics or simple ...

products. These capabilities will support R&D products, AI applications, client intelligence and firm-wide decision support. This is a hands-on hybrid data-engineering and applied-data-science role, with particular responsibility for building data products in Microsoft Fabric and Databricks. You will work with Data Programme colleagues … data assets using agreed patterns, without duplicating enterprise platform responsibilities. You will join a small, hands-on multidisciplinary team working collaboratively across discovery, prototyping, engineering, productionisation and continuous improvement. Key Responsibilities Partner with the Data Programme, data owners and system teams to assess, access and combine priority internal ...

offer . About the role: Join us as a Senior Software Engineer in our critical Account Integrity team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base. How we work … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product. What do you need? Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. System Design & Operation: Proven experience designing and operating CI/ ...

offer. Job Description About the role: Join us as a Senior Software Engineer in our critical Account Integrity team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base. How we work … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product. What do you need? Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. Experience building and designing scalable web applications that handle large ...

offer . About the role: Join us as a Senior Full-Stack Engineer in our critical Account Integrity team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base. The Account Integrity … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product. What do you need? Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. Experience building and designing scalable web applications that handle large ...

roadmaps, align on requirements, and deliver data‐led transformations Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management Provide technical leadership and mentorship through code reviews, design … reviews, best practices, and upskilling across data science and engineering partners Communicate with technical and non‐technical stakeholders, translating model outputs into decisions, tradeoffs, and operational plans Maintain strong documentation for approaches, model cards, runbooks, and operational procedures Required Qualifications, Capabilities, and Skills Master’s degree in a quantitative ...

roadmaps, align on requirements, and deliver data-led transformations Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management Provide technical leadership and mentorship through code reviews, design … reviews, best practices, and upskilling across data science and engineering partners Communicate with technical and non-technical stakeholders, translating model outputs into decisions, tradeoffs, and operational plans Maintain strong documentation for approaches, model cards, runbooks, and operational procedures Required Qualifications, Capabilities, and Skills Master's degree in a quantitative ...

offer. Job DescriptionAbout the role: Join us as a Senior Full-Stack Engineer in our critical Account Integrity team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base. The Account Integrity … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product. What do you need? Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. Experience building and designing scalable web applications that handle large ...

challenge the appropriate methodology, develop technically rigorous solutions and help take them through to operational use. You will work across Data Science, Data Engineering and Analytics, applying advanced statistical, Machine Learning and AI approaches to complex healthcare and organisational problems and ensuring that successful solutions are reproducible, scalable … Data Science is operationalised --strengthening methodological standards, Reproducible Analytical Pipelines, automation, model validation and assurance, and the integration of Data Science with Data Engineering and Analytics. You will have scope to identify high-value problems, determine the appropriate analytical methodologies and help take successful solutions from experimentation through ...

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 … 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 ...

level of experience and qualifications by reading the full overview of this opportunity below. You’ll be central to delivering a robust, high-performing engineering foundation that powers analytics, operational data flows, and future AI capabilities across our global events and digital products. This role is primarily focused … engineering excellence, developing high-quality pipelines, modelling data in line with our Medallion Architecture, and ensuring our Databricks platform is secure, governed, and production ready. Key Responsibilities Design, build, and optimise scalable data pipelines using Databricks, Delta Live Tables, Synapse, and Delta Lake. Develop ingestion, transformation, and orchestration workflows ...