7 of 7 Contract Feature Engineering Jobs in London

realise the full potential of an AI enabled future. Key Responsibilities Build and ship production ready AI/ML features-from data ingestion and feature engineering to model training, evaluation, and deployment Develop LLM/GenAI solutions (prompt engineering, tool use, guardrails) and RAG pipelines (chunking, embeddings … efficient memory/latency tuning Build and maintain MLOps/LLMOps workflows-CI/CD for models and prompts, model registry/versioning, feature stores, and automated promotion across environments Instrument observability for data, models, and prompts (telemetry, metrics, traces, dashboards, alerts); implement A/B tests and online ...

driven decision making across complex digital transformation programmes. Working with modern data platforms, high-quality datasets, and advanced AI frameworks, you will collaborate with engineering, product, and analytics teams to build models that are accurate, explainable, and scalable. The role empowers you to shape end-to-end analytical ecosystems … Collaborate with data engineers, analysts, product managers, and domain experts to translate business requirements into modelling tasks * Build end-to-end ML pipelines, including feature engineering, preprocessing, and deployment-ready outputs * Apply advanced techniques such as NLP, time series forecasting, anomaly detection, optimisation, or LLM/GenAI methods ...

complex digital transformation programmes. With access to modern data platforms, high quality datasets, and advanced statistical and AI frameworks, you will work closely with engineering, product, and analytics teams to build solutions that are accurate, explainable, and scalable. This role empowers you to shape end to end analytical ecosystems … data engineers, analysts, product managers, and domain experts to translate business requirements into well defined modelling tasks Build end to end ML pipelines-from feature engineering and preprocessing to deployment ready model outputs Apply advanced techniques such as NLP, time series forecasting, anomaly detection, optimisation, or LLM/ ...

complex digital transformation programmes. With access to modern data platforms, high-quality datasets, and advanced statistical and AI frameworks, you will work closely with engineering, product, and analytics teams to build solutions that are accurate, explainable, and scalable. This role empowers you to shape end-to-end analytical ecosystemsaccelerating … with data engineers, analysts, product managers, and domain experts to translate business requirements into well-defined modelling tasks. Build end-to-end ML pipelinesfrom feature engineering and preprocessing to deployment-ready model outputs. Apply advanced techniques such as NLP, time-series forecasting, anomaly detection, optimisation, or LLM/ ...

making across complex digital transformation programmes. With access to cutting edge AI frameworks, high performance computing environments, and modern data platforms, you will guide engineering and data science teams in building secure, scalable, and ethical AI systems. This role empowers you to shape end to end AI ecosystems-accelerating … more intelligent, AI enabled future. Key Responsibilities Define the enterprise AI architecture vision and reference patterns; align them to business goals, risk posture, and engineering standards across cloud and hybrid environments Design secure, scalable AI solutions covering data ingestion, feature engineering, model training, inference, and continuous feedback ...

making across complex digital transformation programmes. With access to cutting-edge AI frameworks, high-performance computing environments, and modern data platforms, you will guide engineering and data science teams in building secure, scalable, and ethical AI systems. This role empowers you to shape end-to-end AI ecosystemsaccelerating delivery … more intelligent, AI-enabled future. Your responsibilities: Define the enterprise AI architecture vision and reference patterns; align them to business goals, risk posture, and engineering standards across cloud and hybrid environments. Design secure, scalable AI solutions covering data ingestion, feature engineering, model training, inference, and continuous feedback ...

modelling solutions Contribute to model documentation standards and lifecycle governance Own backlog contributions, user stories and acceptance criteria Drive alignment between business stakeholders and engineering team Skills & Competencies Strong knowledge of energy markets, including supply demand fundamentals, storage, flows and pricing Proven background in energy analytics and forecasting, including … scenario modelling Experience with major energy hubs (e.g., TTF, JKM) and cross-commodity linkage Solid understanding of feature engineering, statistical modelling, and ML workflows Strong Python skills (e.g., pandas, NumPy, Jupyter) Strong analytical thinking with the ability to simplify complex concepts If this sounds like a good ...