Machine Learning Jobs

• London
• Senior
• Permanent

Design and implement generative models that learn intervention effects from single-cell perturbation and multiomic data, focusing on counterfactual prediction and experimental design. Work in interdisciplinary teams with experimental biologists to validate computational hypotheses and guide the highest-signal next experiments, using modern ML tooling and scalable infrastructure.

• London
• On-site
• Entry level
• Permanent

Contributes to the design and execution of cellular and biochemical assays, including arrayed CRISPR perturbation screens, cell culture of primary and immortalised lines, and phenotypic readouts such as flow cytometry, RT-qPCR and ELISA. Also handles data analysis, sample tracking, QC, reagent stocks and lab upkeep, working closely with Discovery and computational colleagues in a matrixed TechBio setting.

CRISPR · Flow Cytometry · RT-qPCR +3

• Sydney, Australia
• Hybrid
• Senior · manages people
• Permanent

Lead high-impact AI projects, defining data science approaches and designing robust software architectures for bespoke client solutions. Mentor junior data scientists, partner with commercial teams on scoping, and ensure delivery rigour while building client relationships across government, finance, retail, energy, life sciences and defence.

Python · NumPy · Pandas +2

• London
• Hybrid
• Senior · manages people
• Permanent

Lead high-impact AI projects for public sector clients, defining data science approaches and designing robust software architectures. Mentor junior data scientists, partner with commercial teams on client relationships, and ensure delivery rigour. Hands-on Python, NumPy, Pandas and deep-learning work, with possible UK Security Clearance and occasional on-site client work.

Python · NumPy · Pandas +2

• London
• Hybrid · 3 days in office
• Lead

Owns the safety assessment strategy for drug discovery projects from inception to regulatory submission, working with small molecule and biologics platforms. Designs screening cascades, authors and defends regulatory toxicology sections, and manages CRO relationships for outsourced wet-lab work. Also guides development of an AI predictive toxicology platform with ML researchers.

AI/ML

• Cambridge, United States
• Hybrid · 3 days in office
• Senior · manages people

Lead medicinal chemistry efforts on drug discovery projects, guiding them from initiation to clinical candidate selection as a Project Lead or Medicinal Chemistry Lead. Partner closely with ML scientists to refine AI models, manage CRO resources, and generate IP, with some roles line-managing 2-4 chemists.

AlphaFold

• London

Lead and contribute to interdisciplinary research programmes on how frontier AI systems influence human decisions, designing large-scale studies, RCTs, model evaluations and benchmarks. Work spans computational social science, AI safety, machine learning and cognitive science, with opportunities to publish and engage policymakers and frontier labs.

Claude Code · Codex

• London
• Hybrid · 1 day in office
• £260,000 – £630,000 pa
• Mid-level

Blends research and engineering to advance reinforcement learning for large language models, building agentic capabilities like computer use and autonomous code generation. Involves architecting distributed RL training infrastructure across GPU clusters, designing novel training environments and evaluations, and profiling and optimizing the stack. Works closely with alignment, red team, and production training groups, with a strong pair-programming culture.

PyTorch · TensorFlow · JAX +3

• London
• Hybrid
• £370,000 – £630,000 pa
• Mid-level

Builds and improves the RL training infrastructure researchers rely on, profiling, debugging and rearchitecting bottlenecks across the stack. Partners with researchers and adjacent engineering teams to ship tooling that speeds up training runs, owning reliability and performance end-to-end.

JAX · PyTorch

• Hatfield
• On-site
• £39,560 – £46,970 pa
• Entry level
• Contract

Postdoctoral role delivering research on innovative AI/ML algorithms for predictive modelling and optimisation of agricultural applications using heterogeneous data, as part of an Innovate UK-funded collaborative project. Duties include developing AI/ML software tools, data management and analysis, supporting the Principal Investigator on project milestones, and contributing to publications and reports.

TensorFlow · Scikit-Learn · PyTorch +1

• Sheffield
• Hybrid
• £32,080 pa
• Entry level
• Contract · Part time

Build and evaluate machine learning models that predict Strep A outbreaks from multiple real-world datasets, turning them into early-warning signals. Work closely with clinicians and an engineering team so analyses feed into a practical public health tool, with emphasis on reproducible Python or R analysis.

• Manchester
• Hybrid
• £48,337 – £59,390 pa
• Mid-level
• Contract

Develops and applies machine-learning and AI methods to protein engineering and enzyme design, analysing large biological, chemical and experimental datasets and building predictive models and computational tools. Works within an interdisciplinary group spanning the Manchester Institute of Biotechnology and Department of Chemistry, providing ML and data-science expertise, training and support to postdocs and students, and contributing to publications and funding bids.

• United Kingdom
• Remote
• Mid-level
• Permanent

Owns the data infrastructure behind frontier AI models, building large-scale pipelines for collecting, filtering and transforming training datasets. Also trains classifiers, quality filters and labeling models, and designs curation strategies like deduplication and quality scoring. Fully remote, with tooling work letting researchers explore and train on massive datasets.

Kubernetes

• United Kingdom
• Remote
• Mid-level
• Permanent

Join the research team at an AI audio company, training state-of-the-art models across modalities and improving them through post-training, data curation and architectural changes. You'll design rigorous benchmarks and evaluations to judge whether new model iterations are genuinely better, working autonomously in lean, high-velocity teams.

GitHub

• London
• Hybrid
• Senior

Develops production-grade ML models and pipelines for physics simulation, working with research scientists and simulation engineers. Involves scaling training and inference across multi-GPU/multi-node distributed systems, optimising from job scheduling down to CUDA/Triton/Warp kernels, and building cloud infrastructure on CoreWeave and AWS.

AWS · Azure · GCP +7