Machine Learning Jobs

• 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

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

Lead computational drug design programs from hit identification through to candidate nomination, applying AI-first approaches and shaping the ML drug design engine alongside ML scientists. Roles span Program Lead or Computational Chemistry Lead, with some positions managing 2-3 computational chemists. Hybrid working in Cambridge, MA, three days a week in office.

REINVENT

• Cambridge, United States
• Hybrid · 3 days in office
• Lead

Lead DMPK strategy across drug discovery projects, designing screening cascades and mechanistic experiments while integrating PK, PD and toxicology data for dose and safety predictions. Work with AI/ML platform teams to optimise ADME models and author regulatory DMPK sections, in a hybrid Cambridge, MA role.

Python · R

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

Join the model performance and scaling team to implement and optimize LLM post-training methods on frontier models, working with research teams to turn new methods into production systems. The role focuses on distributed training and inference performance, low-precision methods, and frameworks like JAX or PyTorch, in a hybrid London setting.

JAX · PyTorch · NCCL +5

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

Own, secure and scale a suite of self-hosted, multi-user vendor applications across cloud environments. Day to day you build Kubernetes deployment pipelines, maintain Terraform IaC, run container and dependency security scanning, remediate CVEs, and configure SSO/RBAC via SAML 2.0 and OIDC, bridging integration, operations and security.

Kubernetes · GitHub Actions · GitLab CI +7

• Cambridge, United States
• Hybrid · 3 days in office
• Lead

Lead the safety assessment strategy for small molecule and biologic drug discovery projects from inception to regulatory submission, designing screening cascades and mechanistic experiments. Partner with machine learning researchers to build predictive toxicology models and manage external CROs for all wet-lab data generation, while mentoring junior scientists.

KNIME · Python

• Cambridge, United States
• Hybrid · 3 days in office
• Mid-level

First Technical Program Manager hire for the Drug Design and Medical Research function, supporting small molecule drug discovery programs in Cambridge, MA while integrating with the London office. Responsibilities span program planning, timeline monitoring, risk reporting, budget forecasting and spend tracking, CRO and external partner liaison, and embedding operational processes across teams.

Jira · Confluence

• London
• Hybrid · 3 days in office
• Lead

Lead the development and execution of (pre)-formulation strategies for small molecules across drug discovery and preclinical development, designing technologies such as solid dispersions and co-crystals to optimise solubility, stability and manufacturability. Work within an interdisciplinary team alongside AI/ML drug design platform specialists, leveraging external CRO resources and authoring regulatory submissions.

ICH · ASAP · FDA

• 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
• Lead

Lead medicinal chemistry strategy across drug discovery programmes, from hit identification through lead optimisation to candidate nomination, while working hands-on as an individual contributor. Partner closely with AI/ML platform teams to shape predictive models, manage CRO resources and represent the company externally.

AlphaFold

• London
• Hybrid · 3 days in office
• Lead

Builds and evolves a large-scale ML infrastructure platform that supports training and deploying novel models across vast compute and data pools. Works closely with engineering, research and product teams, and explores deploying agents to improve platform robustness. Requires strong Python and experience scaling complex systems, with ML or Kubernetes exposure a plus.

Kubernetes · Google Cloud Platform · GCP

• London
• Hybrid · 3 days in office
• Senior

Join a newly formed LLM Engineering team to architect, implement and own systems bringing large language models into scientific and business processes. Work spans LLM serving stacks, agentic infrastructure, RAG, evaluation frameworks and fine-tuning, partnering with researchers to translate scientific needs into technical AI specifications.

vLLM · GCP · MCP

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

Join a newly formed Scheduling team to own and extend systems that orchestrate compute allocation for complex ML workloads on Kubernetes. You'll design scheduling policies like gang scheduling and topology-aware placement, build custom Kubernetes controllers and CRDs, and partner with ML researchers to optimize GPU and TPU utilization.

Kubernetes · Kueue · Volcano +5

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

Join the Compute Infrastructure team to keep a planet-scale GPU accelerator fleet healthy and efficient. You'll build observability and telemetry pipelines, automate recovery, hunt compute waste, and optimise accelerator utilisation for large-scale training and inference, working closely with ML infrastructure and research teams.

GCP · Kubernetes · Nvidia GPU +1

• London
• Hybrid · 3 days in office
• Lead

Technically lead the Platform group, designing, operating and refining research, development and production cloud infrastructure across GCP, Kubernetes, Docker and Terraform. The role spans core technical decisions, tooling and CI/CD processes, working closely with scientists, ML researchers and product teams, and reports directly to the Director of Engineering.

GCP · Kubernetes · Docker +7