Machine Learning Jobs

• London
• £25,000 – £45,000 pa
• Entry level

A self-paced traineeship taking complete beginners through AI fundamentals, Python, data handling, machine learning and Git/GitHub, with Microsoft AI-900 certification and two tutor-assigned industry projects. On completion, candidates are placed into a Junior AI Engineer role within 20 miles of their location, with training designed to fit around existing work or unemployment.

Microsoft AI-900 · Azure AI Fundamentals · Git +1

• Rochdale
• £25,000 – £45,000 pa
• Entry level

A self-paced traineeship that takes complete beginners through AI fundamentals, Python, data handling, machine learning and Git/GitHub, plus Microsoft AI-900 certification and two tutor-assigned industry projects. On completion, candidates are placed into a Junior AI Engineer role with an employer within 20 miles of their location.

Microsoft Azure · Git · GitHub

• London
• Hybrid
• Senior
• Permanent

Own end-to-end technical program delivery for UK public sector and defence customers, from initial deployment through production scaling, acting as the bridge between frontier AI capabilities and government requirements. Navigate procurement, security authorisations, data sovereignty and compliance while coordinating Applied ML, Forward Deployed Engineering, Platform and Product teams. Work spans air-gapped, on-premises and highly regulated environments.

Azure · AWS GovCloud

• London
• Hybrid
• Permanent

Owns the evaluation strategy for an enterprise AI workspace, building evals that capture agentic workflows, tool use and knowledge work. Translates user feedback, production failures and usage logs into continuous measurement, then feeds model failures and capability gaps back to central modelling teams. Sits between product, customer-facing and research teams rather than being pure research or product engineering.

North

• London
• Remote
• Entry level
• Temporary

A four-month, full-time research fellowship focused on empirical AI safety and security projects, using external infrastructure like open-source models and public APIs. Fellows receive direct mentorship from Anthropic researchers, join a shared workspace or work remotely, and aim to produce a public output such as a paper submission.

Large Language Models · Deep Learning Frameworks

• London
• Lead · manages people
• Permanent

Lead the science vision for Trusted Supply, safeguarding advertiser trust across Amazon Advertising by developing algorithms for brand safety, suitability scoring, fraud detection, viewability prediction and privacy-preserving measurement. The role spans multi-year research direction, publication roadmaps, cross-team modelling frameworks and production systems serving billions of ad impressions daily, alongside hiring and mentoring applied scientists and research engineers.

• London
• Hybrid · 3 days in office
• Senior · manages people

Lead and contribute to core machine learning research applying large language models to drug discovery, developing and refining LLM-driven approaches across biology and chemistry problems. Work spans post-training, reasoning, test-time scaling, tool-use, alignment, agents and reinforcement learning, with model training and inference engineering in JAX, PyTorch or TensorFlow. Depending on experience, you may also lead standalone projects, mentor ML researchers and shape the research roadmap.

JAX · PyTorch · TensorFlow +3

• London
• Hybrid · 3 days in office
• Senior · manages people

Builds greenfield machine learning models and algorithms for drug discovery, designing new architectures, running experiments and scaling training and inference frameworks. Works in an interdisciplinary team of ML scientists, engineers and domain experts, with opportunities to lead projects and mentor others depending on experience.

JAX · PyTorch · TensorFlow +3

• London
• Hybrid
• Lead
• Permanent

Owns the autonomy performance measurement framework for a public-scale robotaxi deployment, defining metrics, dashboards and release gates for an end-to-end learned driving system with no existing playbook. Runs the detect-triage-root-cause-fix loop across model, robot software, backend and evaluation tooling, leading cross-functional teams without direct authority while staying hands-on in Python, C++ and SQL.

Databricks · Looker · Grafana +2

• London
• Hybrid
• Lead

Own the product strategy for the runtime that serves conversations in production, the inference layer hosting models, and the data platform feeding both. Set build-vs-buy and self-host-vs-managed direction, define evaluation frameworks for latency, throughput and cost, and partner directly with infrastructure engineering leadership on a roadmap with no customer-facing surface.

Raven

• London
• Hybrid
• Director
• Permanent

Owns the architecture, strategy and integrity of safety cases for robotaxi and OEM ADAS products, defining top-level claims, argumentation structures and evidence traceability. Sits independently from Engineering and Product, providing expert challenge and oversight across AI/ML, systems, validation and operational safety. Focuses on safety arguments for AI-enabled autonomous driving, including functional safety, SOTIF and post-deployment monitoring.

ISO 26262 · ISO 21448 · ISO/PAS 8800 +2

• London
• Hybrid
• Junior
• Permanent

Supports delivery of bespoke AI solutions for pharmaceutical and life sciences clients, managing individual work streams, analysing stakeholder requirements and translating operational needs into user stories for engineering teams. Involves open-source analysis, workflow design and testing, and close collaboration with technical teams in a small, client-facing team.

Metaview

• United Kingdom
• On-site
• Entry level
• Permanent

Join a multidisciplinary applied science team tackling optical and photonic challenges across defence, healthcare and energy. Day-to-day work spans lab experimentation and desk-based analysis, with a central focus on designing and developing photonic integrated circuits, plus free-space optics, fibre systems or photonic devices. Tailored training is provided for those without an integrated photonics background.

Ansys Lumerical · Zemax · Python +1

• London
• £23,805 pa
• Entry level
• Contract

Develop a framework combining a differentiable reacting flow solver with a machine learning-based controller to anticipate and mitigate extreme events such as flashback and thermoacoustic instabilities in hydrogen and SAF combustion. The role sits within the European CONTEXT project at the intersection of scientific machine learning and fluid dynamics, using high-fidelity simulations and Imperial's HPC facilities.

HPC

• Exeter
• £21,805 pa
• Entry level
• Contract

Develops a multiscale Scientific Machine Learning digital-twin framework to predict thermal trajectories, torque capability and efficiency in low-speed, high-torque electric propulsion. Combines physics-informed neural networks, neural state-space models and Neural ODEs, validated through safety-constrained dynamometer experiments at the Centre for Future Clean Mobility and on-site work with a marine power-systems partner.

Neural Ordinary Differential Equations · Deep Neural Networks · Recurrent Neural Networks +1