Jobs at Isomorphic Labs

Operate and secure self-hosted multi-user vendor applications: deploy and maintain Kubernetes-based instances, build CI/CD pipelines and IaC, integrate SSO/RBAC, run vulnerability scanning and remediation, automate rollouts across endpoints, and manage monitoring, backups, and low-downtime upgrades.

As a Research Scientist focused on Large Language Models, you'll develop and apply advanced ML techniques in drug discovery, contributing to groundbreaking research and leading projects in a collaborative environment.

Lead global internal communications and employee engagement strategy, advise executives on high-stakes messaging, design multi-channel campaigns, run flagship events (town halls, offsites), modernise channels with AI experimentation, measure engagement via dashboards, and manage a comms specialist to deliver culture-building programs.

Manage company-wide internal communications channels, produce and publish newsletters and updates, support multimedia asset creation and basic video editing, build presentation slides, run end-to-end event logistics and vendor coordination, track engagement metrics, and help develop creative internal campaigns to strengthen culture and employee connection.

Isomorphic Labs seeks to recruit interested candidates for roles in software engineering, machine learning research, computational chemistry, and project management for future openings.

Lead bioanalytical strategy across small molecules, biologics, and ADCs from discovery through preclinical GLP/non-GLP studies. Design, validate, transfer PK/PD and ADA assays, manage global CROs and complex cold-chain logistics, integrate bioanalytical data with AI models, author IND/IB bioanalytical sections, and represent bioanalysis in cross-functional teams to advance candidates to clinic.

As a Software Engineer, you will design and manage cloud infrastructure, enhance DevOps practices, and collaborate with teams to drive innovation in drug discovery.

The Principal Software Engineer will ensure the reliability and scalability of AI systems, leading infrastructure improvements and optimizing ML workflows.

Design and develop novel machine learning models and training algorithms for drug discovery. Lead and run research projects, implement and scale training/inference frameworks, analyze experiments, and collaborate across disciplines. Mentor and provide technical guidance to other ML researchers and contribute to research direction and presentations.

Build, operate, and optimize a high-throughput inference platform serving large ML models. Harden and scale inference services, drive architectural tooling decisions, collaborate with research and applied ML teams, and deliver well-tested, reliable features for production model serving.

As a Research Engineer, you will develop and optimize AI models for drug discovery, collaborating with scientists to advance ML applications in biopharmaceuticals.