Machine Learning Jobs

Cambridge Consultants · United Kingdom

Work on multidisciplinary engineering projects across consumer, industrial, and defence sectors, designing embedded systems, writing firmware in C or SystemVerilog, and developing hardware for innovative products. Engage in full project lifecycles from requirements to handover, with mentorship to grow technical and systems design expertise. Projects include robotics, AI-driven security solutions, and collaborative product development with major clients.

Isomorphic Labs · London

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.

Cohere · London

Research engineering role on the integration team, building and scaling machine learning algorithms and infrastructure for LLM post-training, with a focus on large-scale distributed RL methods. Day to day involves writing high-performance training software, developing research tooling, and collaborating with infrastructure, efficiency, serving and scientific teams to improve SFT, offline preference and RL training cycles.

Relation Therapeutics · London

Builds and scales generative and predictive models of cellular behaviour, acting as the bridge between ML theory and implementation. Day to day involves optimising large neural networks, distributed multi-GPU/multi-node training, profiling GPU workloads, and productionising research code for multi-modal biological data.

TTP · Cambridge

Consultants design and deploy machine learning systems for diverse defence and security projects, from proofs-of-concept to working prototypes. The role spans literature analysis, model training, rapid prototyping and experiment design, often combining science, engineering and ML in novel settings. Work is on-site in Cambridge within a flat, collaborative team of around 40 specialists.

Anthropic · London

A four-month, full-time research fellowship working on empirical AI projects in either ML systems/performance or reinforcement learning, using external infrastructure like open-source models and public APIs. Fellows receive direct mentorship from Anthropic researchers and aim to produce a public output such as a paper submission, with projects spanning CPU simulators, accelerator backends, synthetic data pipelines, and RL environments.

Cohere · London

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.