Isomorphic Labs

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

Lead a team of biologists in the Exploratory Sciences group, owning in vitro pharmacology strategy for novel modalities such as TPD, molecular glues and peptides. Design screening cascades and quantitative assays, set ML-ready data standards, and champion LLM agentic workflows while managing CRO and academic studies.

SPR · GCI · nanoDSF +5

• 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

• 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

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