11 of 11 Remote/Hybrid Feature Engineering Jobs in London

workflows, and develop containerised model services that integrate directly into the OneView platform. This includes hands‐on work with model architectures, feature engineering, model optimisation, performance debugging, schema‐aligned data preparation, and ML‐driven interfaces. This is a role for engineers who want to build and maintain real … real systems, and solve real operational ML problems – not just prototypes. You will work directly with production data, client technical teams, and our internal engineering ecosystem to deliver AI components that are robust, scalable, and deployed into live environments. Key Responsibilities Machine learning engineering Design, train and optimise ...

hire has very meaningful impact.They are looking for a Senior Data Scientist to lead the predictive analytics capability and their critical programme.You’ll design feature engineering pipelines, select and validate classification and regression models, and establish rigorous evaluation methodology (targeting AUC-ROC 0.85) across a 300M+ point education … explainable and production-ready.Core Responsibilities: Predictive Model Development : Build and validate supervised learning models (classification & regression) using complex, multi-source, time-series-influenced data. Feature Engineering : Design scalable feature pipelines across attendance, behaviour, wellbeing, assessment and SEND datasets. Evaluation & Methodology : Establish rigorous evaluation frameworks including ...

building, and deploying scalable machine learning solutions to enable advanced analytics, automation, and decision-making across complex government systems. This is a hands-on engineering role, working closely with data scientists, analysts, architects, and product teams to productionise models, build data pipelines, and embed ML capabilities into live services. … Synapse) Experience in AWS environments is beneficial Experience with MLOps practices and tools (CI/CD pipelines, model monitoring, versioning) Strong understanding of data engineering concepts (ETL pipelines, data lakes, feature engineering) Experience working with large-scale structured and unstructured datasets Knowledge of AI ethics, bias mitigation ...

/ML features, from data ingestion and training to deployment, MLOps workflows, CI/CD, and model versioning Develop LLM/GenAI solutions: prompt engineering, RAG pipelines, embeddings, vector search, and inference optimisation (LoRA/PEFT, quantisation, GPU/TPU) Own observability across data, models, and prompts … Responsible AI practices throughout What you'll need Hands-on LLM/GenAI experience (Gemini or open source) including fine-tuning, RAG pipelines, prompt engineering, and graph-based workflows (ADK, MCP) Strong Python, API/microservices development, GCP (Vertex AI, BigQuery), CI/CD, and containerisation (Docker, Kubernetes) Nice ...

governance frameworks to ensure responsible AI/ML model deployment. Use Python to automate processes and optimise workflows. Handle large datasets, including data preprocessing, feature engineering, and model evaluation. Lead the agile development of AI solutions from concept through deployment and ongoing improvement. Create and maintain comprehensive technical … documentation. Communicate complex AI concepts clearly to stakeholders at all levels. What you'll bring: Proven experience (3 years) in AI solution engineering, with a focus on large language models, prompt engineering, and RAG implementations. Strong skills in data analytics, MLOps practices, and API development. Knowledge of governance ...

problem definition through to deployment in live environments. * Design, build, and deploy machine learning models within Pega-based decisioning platforms. * Lead model development across feature engineering, training, validation, and ongoing performance monitoring. * Work closely with application and logic developers to embed models into operational decision workflows. * Develop statistical ...

Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions Contribute to the development of data pipelines and feature engineering workflows Integrate models into production using APIs, batch jobs, or real-time systems Apply best practices around experimentation, evaluation, versioning, and monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

Function focused on embedding AI into the core of how products are designed, engineered, delivered, and supported. This is not a traditional 'AI feature engineering' role. You'll help shape AI-native ways of working across the business - designing agentic workflows, integrations, and orchestration layers that connect teams … systems, and stages of the product lifecycle. The focus is on building intelligent systems that reduce friction, surface context, automate workflows, and improve how engineering, QA, delivery, sales, and product teams operate together. What you'll be doing: Designing and building agentic AI workflows across multiple business functions Building ...

unlock new capabilities for our market-leading suite of trade surveillance products. This role will see you combine hands‐on model development and software engineering, and collaborate with a high-performing team of Quant Researchers and Developers as well as other cross-functional departments. Responsibilities Design, develop, and deploy … linear regression, reinforcement learning and deep learning Industry experience using Large Language Models (LLMs) to deliver commercial value Experience building data pipelines and performing feature engineering on real-world datasets Strong problem-solving skills and attention to detail Good understanding of SQL and working with complex datasets Keen ...

Function focused on embedding AI into the core of how products are designed, engineered, delivered, and supported. This is not a traditional 'AI feature engineering' role click apply for full job details ...