Isomorphic Labs

Isomorphic Labs

Visit websiteLinkedIn201-500 employees

Open Positions at Isomorphic Labs

6 open positions

London, United KingdomSenior

Build the curated, version-controlled biological data layer that powers Isomorphic Labs’ machine learning and drug discovery programs. You’ll develop scalable bioinformatics pipelines and partner with research teams to turn complex biological data into reliable ML-ready datasets.

1 day ago
London, United KingdomSenior

Build the data platform powering Isomorphic Labs’ AI-driven drug discovery research. You’ll engineer scalable data services, scientific data pipelines, and research infrastructure while partnering closely with scientists and machine learning researchers.

London, United KingdomSenior

Join Isomorphic Labs’ LLM Engineering team to build scalable, secure infrastructure that brings large language models and agentic workflows into scientific discovery and business processes. You’ll combine production software engineering, LLM serving, evaluation, tooling, and model refinement in a highly interdisciplinary environment.

10 days ago
London, United KingdomSenior

Build and operate the cloud infrastructure and developer tooling that powers Isomorphic Labs’ AI-driven drug discovery platform. This hands-on TechOps role spans Kubernetes, cloud infrastructure, automation, observability, and software lifecycle improvements.

DockerGitHub ActionsGoogle Cloud PlatformGrafanaHelmKubernetes+4 more
1 month ago
London, United KingdomSenior

Lead AI security engineering for Isomorphic Labs’ frontier drug-discovery platform, securing models, agentic workflows, and distributed ML infrastructure. The role combines adversarial threat modeling, AI guardrails, incident response, and automated governance.

2 months ago
London, United KingdomMid Level / Senior / Staff+

Join Isomorphic Labs as an ML Research Engineer building and optimizing frontier AI models for drug discovery and computational biology. You will work with research scientists and engineers on foundational models, experiments, evaluation systems, and production-scale ML infrastructure.

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