26 to 50 of 111 Feature Engineering Jobs in London

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph Understanding of model evaluation, validation techniques, and production monitoring Experience working ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph Understanding of model evaluation, validation techniques, and production monitoring Experience working ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph Understanding of model evaluation, validation techniques, and production monitoring Experience working ...

Full time: Posted Yesterday: R-166923### **Job Description**## Overview Join a genuinely collaborative team whose diverse expertise delivers innovative solutions to complex engineering challenges worldwide. As an experienced data scientist, you will work across the data lifecycle in a fast-paced Agile environment, helping keep people, critical businesses … data products. The role requires a strong foundation in data science together with practical experience operating within modern data platforms, MLOps environments and software engineering workflows. ## Your role **Data Science & Analytics*** Design, develop and deploy statistical, insightful, AI and machine learning solutions to solve operational challenges.* Explore large ...

team in Sheffield This role is hands on and suited to someone who can lead by example partner with stakeholders and help shape engineering standards while delivering high-quality software at paceHybrid working:The places that you work from day to day will vary according to your role, your … noting that you will be unable to work at home 100% of the time.Your Role:Provide technical direction mentoring and code review leadershipDrive good engineering practices testing documentation maintainability securitySenior full stack engineering capability with a strong frontend foundationReactJS and TypeScriptStrong backend engineering mindset API design integration ...

into one unit that will drive cutting-edge development in a number of critical areas for the business. The role sits within the Data Engineering team and reports to the Head of Data Engineering. The team’s remit is to drive innovation & revenue through the development & delivery of revenue … generating/client-facing data engineering solutions used across the agency. The Senior Data and ML Engineer will be part of a growing team that delivers highly impactful data solutions across our extensive client portfolio and also the agency’s own product offerings. We seek individuals who are proactive ...

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. 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 ...

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 ...

ability to leverage data, knowledge, and prediction to find new medicines. We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data/metadata/knowledge platforms, and AI/ML and analysis platforms, all geared toward: Building a next-generation, metadata … data mechanics" Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time ...

EngineeringorEquivalent experience that shows you can deliver resultsTechnical skillsCore skillsStrong Python and SQL, with clean, maintainable codeSolid understanding of ML fundamentals. For example feature engineering, model selection, handling imbalanced data, choosing and interpreting metricsExperience with PyTorch or TensorFlowGenAI specificHands on experience with LLM APIs or open source models … provider. AWS, GCP or AzureFamiliar with Docker and CI/CD pipelinesExperience with managed ML platforms such as SageMaker, Vertex AI or Azure MLData engineering and MLOpsExperience with data warehouses such as Snowflake, BigQuery or RedshiftWorkflow orchestration using tools like Airflow or DagsterExperience with MLOps tools such as MLflow ...

ability to leverage data, knowledge, and prediction to find new medicines. We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data/metadata/knowledge platforms, and AI/ML and analysis platforms, all geared toward: Building a next-generation, metadata … data mechanics” Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time ...

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 ...

analytics team & Tech partners in research to define the knowledge system, the agentic layer across the enterprise. You bring deep, hands-on AI/engineering expertise and the judgement to turn ambiguous technical problems into shipped, production-grade systems, while mentoring the engineers around you. Key Responsibilities This role … first production versions directly for use cases where the path is clear - before the Sr. Solutions Engineer takes them forward to scale. AI-Native Engineering Operate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery - selecting the right level of automation for each engagement. ...

allow ML teams to move from research to production quickly, safely, and cost-efficiently. You’ll partner closely with Applied Science, Data, Product, and Engineering leadership to build a scalable, secure, and observable ML platform that powers multiple business lines. Your impact will come not only from the systems … growing ML and GenAI adoption across multiple teams, products, and business lines. Lead the architecture of platform capabilities across the full ML lifecycle: experimentation, feature engineering, artifact management, training, deployment, monitoring, retraining, and governance. Design cloud-native infrastructure for distributed training and inference, including GPU-based environments, autoscaling ...

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 ...

Your Impact Customer Onboarding & Engine Customization: Lead the technical deployment of our engines for new clients. Partner closely with customers, Customer Success, Product, and Engineering to adapt and customize ML models, ensuring they accurately reflect client-specific business logic, operational guardrails, and unique data nuances. Analytic Engine Development: Design … implement robust Machine Learning (LightGBM, XGBoost) and Deep Learning (PyTorch) models specifically focused on complex demand sensing and resolving cold-start forecasting problems. Feature Engineering Pipelines: Build and optimize scalable data pipelines leveraging a hybrid SQL/Python architecture (dbt, Snowflake) to extract rich, localized temporal signals from ...

applications in relevant domains like image recognition, natural language processing, or recommender systems. Data Science: Strong foundation in data science principles, including data analysis, feature engineering, model training, evaluation, and deployment. Programming Languages: Expertise in Python for data manipulation, model development, and scripting. Cloud Platforms: Experience with cloud … retail domain (e.g., text and image analysis , pricing models , recommender systems etc). Engineer and maintain data pipelines for data acquisition, cleaning, transformation, and feature engineering. Train machine learning models using various algorithms. Integrate machine learning models into our existing infrastructure and applications. Leverage existing LLMs based ...

/ML, including leading teams and projects from conception to production Strong foundation in AI/ML concepts and practical experience with data analysis, feature engineering, and model development Experience working with large, complex datasets and applying statistical analysis Hands-on experience training, deploying, and maintaining machine learning ...

doing:Design, build and operate machine learning systems that support customer engagement, marketing effectiveness, pricing and commercial decision-making.Own the end-to-end engineering lifecycle of machine learning products, including data ingestion, feature engineering, deployment, monitoring and optimisation.Productionise advanced machine learning solutions and ensure they operate reliably … scale.Partner closely with Applied Scientists to translate research and experimentation into scalable production systems.Help shape the future of our MLOps platform by contributing to engineering best practices, operational excellence and platform capabilities.Build reusable tooling, frameworks and infrastructure that accelerate machine learning delivery and reduce operational overhead.Influence technical direction ...

Build and deploy machine learning models across forecasting, customer segmentation, and propensity modelling Own projects across the full model lifecycle, from data exploration and feature engineering through to deployment and monitoring Partner with Product, Engineering, and commercial teams to deliver scalable analytical solutions Translate complex findings into … with AI-assisted development tools such as GitHub Copilot, Claude, Codex, or similar to improve productivity and code quality Understanding of LLM applications, prompt engineering, and practical AI use cases within analytics workflows Excellent stakeholder management skills with the ability to translate technical outputs into clear business recommendations ...

Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve … will play a pivotal role in designing and implementing modern, scalable data solutions for our clients. Working closely with colleagues across the Data & Analytics Engineering teams, you will help architect, build, and optimise new data platforms or migrate existing solutions to Google Cloud. This is an exciting opportunity ...

office) Package: £80,000-100,000 + 30% Bonus + 10% Shares + Benefits (see more below) About Appvia Appvia is a specialist platform engineering and AI enablement consultancy, helping organisations design, build, and operate modern cloud platforms and transform how software is delivered. Our work spans platform engineering … Solutions Architect to help shape and grow Appvia's Data & AI capability. This is a high-impact role sitting at the intersection of Revenue, Engineering, and Product. Working closely with the Head of Cloud Solutions and the growing Data & AI Practice, you will help customers turn data into decisions ...