Machine Learning Jobs

• London
• Hybrid · 3 days in office
• Lead

Drive DMPK strategy across drug discovery projects, designing screening cascades and mechanistic experiments with an AI-first approach. Integrate DMPK, PD and toxicology data to predict human dose and safety windows, and author regulatory documents. Work closely with Chemistry, Pharmacology and AI/ML platform teams on multiple modalities including biologics and peptides.

R · Python · KNIME

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

Lead computational chemistry strategy across drug discovery programs, applying AI-first approaches to hit finding, molecular design and lead optimisation. Work with ML scientists to embed generative models into cheminformatics workflows, with some roles managing 2-3 computational chemists.

REINVENT · AlphaFold · Large Language Models

• United Kingdom
• Remote
• Senior

Serves as the primary technical contact for academic and research partners, driving adoption of NVIDIA's accelerated computing and AI stack. Works hands-on with researchers on large language model training, fine-tuning, inference and agentic workflows at supercomputing scale, delivering workshops and mentoring power users. Involves around 30% travel and close collaboration with research labs and university faculty.

NVIDIA AI Enterprise · NeMo Framework · Megatron Bridge +7

• United Kingdom
• Remote
• Mid-level
• Permanent

Builds and scales data pipelines from ingestion to delivery, implementing dbt best practices, data standards and quality controls. Develops self-service tooling and documentation so teams across Engineering, RevOps and Growth can access data independently, and creates AI agents to answer data questions. Works remotely within a lean, high-velocity data team.

dbt · Python · SQL +2

• London
• Remote
• Permanent

Embedded with strategic customers, you own end-to-end delivery of complex integrations, from technical architecture and product features to full-scale builds. The role pairs hands-on Python and API work with daily collaboration with customer engineers and executives, and involves regular travel for customer onsites.

ElevenLabs

• London
• Hybrid · 3 days in office
• Senior
• Permanent

Lead complex end-to-end deployments of frontier models for strategic customers, owning discovery, scoping, system design, build and production rollout. Build full-stack systems in Python or JavaScript, embed with customer teams, and feed field learnings back into product and model roadmaps. Hybrid London role with up to 50% travel.

LLMs · Generative Models

• London
• Hybrid · 3 days in office
• Mid-level
• Permanent

Join OpenAI's Training team in London to push the frontier of LLM development for flagship models, enhancing intelligence, efficiency, and adding new capabilities. The role involves designing and scaling new architectures, running experiments, debugging regressions, and optimizing model and computational performance, with a hybrid schedule of three days in the office per week.

• Solihull
• £45,000 – £62,000 pa
• Permanent

Research and develop AI/ML approaches for power electronics, designing, modelling and simulating converter systems (AC/DC, DC/DC, DC/AC) using tools such as MATLAB, PLECS or Ansys. The role sits at the intersection of power electronics and artificial intelligence, translating academic research into practical engineering applications across electric vehicles, rail and renewable energy.

MATLAB · PLECS · Ansys

• Filton
• £45,000 – £58,000 pa
• Permanent

Research, develop and evaluate image processing and computer vision algorithms within a specialist team, applying AI and deep learning to segmentation, object detection, tracking and classification. Work spans optical flow, pose estimation, particle filtering and computational imaging using MATLAB, Simulink and Python with PyTorch, collaborating with multidisciplinary engineers to turn research into practical applications.

MATLAB · Simulink · Python +1

• Bristol

Research, develop and evaluate image processing and computer vision algorithms for complex weapon systems, using imaging sensors for situational awareness and precision targeting. Work spans tracking, optical flow, deep learning and computational imaging, built mainly in Matlab/Simulink and Python with PyTorch, within a collaborative department linked to MBDA sites in France and Germany.

MATLAB · Simulink · Python +1

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

An interdisciplinary PhD developing miniaturised, low-power sensing hardware co-designed with AI for monitoring wild animal behaviour, including individual recognition and automated quantification of responses. Systems are benchmarked in controlled conditions then validated on wild jackdaws and field sites in West Africa, spanning ecology, electronic engineering and data science.

Thermal Imaging · AI · Machine Learning

• London
• Hybrid · 2–3 days in office
• Mid-level

Build the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develop solvers in differentiable or GPU-native frameworks like JAX or Warp, using commercial and open-source CFD tools, while collaborating closely with ML researchers in a research team.

JAX · NVIDIA Warp · OpenFOAM +2

• London
• Remote
• Entry level
• Temporary

Four-month full-time research fellowship focused on empirical AI safety and security projects, using open-source models and public APIs to produce public outputs such as paper submissions. Fellows receive direct mentorship from Anthropic researchers, access to shared workspaces in London or Berkeley, and work alongside the broader AI safety community.

PyTorch · TensorFlow

• London
• Remote
• Temporary

Four-month, full-time research fellowship working on empirical ML systems or reinforcement learning projects, 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 accelerator backends, synthetic data pipelines, and RL environments.

Claude

• London

Owns the product capability for post-training LLMs, turning research methods into deployable model improvements for customers. Builds reliable training harnesses, synthetic-data pipelines and evaluation workflows, applying SFT, preference optimisation, RLHF/RLAIF and verifier-based approaches. Works closely with Research and platform teams, with a roadmap spanning SaaS, VPC and air-gapped deployments.

PyTorch · LLMs · SaaS +1