Machine Learning Jobs

Cambridge Consultants · United Kingdom

Six- to twelve-month AI and algorithms internship for PhD or Master's students, working alongside engineers on client projects involving modelling, training, testing and data wrangling. Interns also contribute to internal R&D, building on state-of-the-art AI literature, and present results to colleagues and clients. Requires strong Python, Git and demonstrable research experience, plus UK security clearance eligibility.

Cambridge Consultants · United Kingdom

Take technical ownership of AI projects for defence and security clients, designing and building agentic systems that search, interpret and act on information. Lead smaller projects, mentor junior engineers, and work directly with clients on proposals and new work. Requires SC clearance and UK residency.

NVIDIA · Zürich, Switzerland

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts from industry and academia to analyse and optimise complex AI and HPC algorithms on CPU and GPU architectures. The intern also publishes optimisation techniques via developer blogs or conferences and helps influence next-generation hardware, software and programming models.

NVIDIA · Zürich, Switzerland

Design, develop and optimise GPU/CPU-accelerated data processing libraries such as DALI and nvImageCodec, covering numerical methods, performance tuning and benchmarking across architectures. Works closely with leadership and external partners on technical roadmaps while providing technical leadership and guidance to other library engineers.

Isomorphic Labs · London

Research Engineers build and optimise state-of-the-art AI models for drug design, working across the full ML lifecycle from experimentation and evaluation to production deployment. The role involves developing robust codebases, data pipelines and training infrastructure, with a focus on architectures such as Transformers, GNNs and diffusion models, in close collaboration with scientists and engineers.

Anthropic · London · £325,000 – £390,000 pa

Builds and operates the distributed systems that serve Claude to millions of users, spanning request routing, load balancing, autoscaling and fleet orchestration across thousands of AI accelerators in multiple clouds. The role sits at the intersection of high-performance infrastructure and ML, integrating new accelerator platforms and supporting new model architectures.

Isomorphic Labs · London

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.

Ocado · London

Owns the software engineering that brings data science and machine learning products into live production for the Autoplanner team, building AI-powered planning systems across global warehouses and last-mile assets. Writes typed, well-tested Python (with some Java for OSP integration), builds APIs and data contracts, manages AWS deployments and CI/CD, and packages, serves and monitors ML models. Acts as engineering partner to data scientists and shares on-call support.

Cohere · London

Hands-on research and engineering role on the Agent Code team, developing code-generating LLMs and autonomous agent systems for enterprise use. Involves training code models, building agent frameworks for inference and sampling, creating SFT trajectories, working on RL algorithms, and designing benchmarks, in collaboration with the pretraining team on frontier compute infrastructure.

Cohere · London

Drive safety research for agentic LLMs, focusing on data generation, post-training algorithms and evaluation methods so models that access external tools and act in the world remain fair, trustworthy and secure. Work with cross-functional ML, data annotation, product and policy teams on a small, autonomous team, requiring strong statistics, software engineering and Python/PyTorch skills.

Amazon · London

PhD students join an Amazon Science team to own an end-to-end research project, from scoping with a mentor to deploying algorithms, models or systems into production. Projects span computer vision for Prime Video quality, multimodal AI for Rufus, automated reasoning and formal verification, observability for distributed systems, and recommendation models. Interns may publish at top-tier conferences or see their work ship before the internship ends.

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.