The opportunity
Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist who combines deep chemistry knowledge with machine learning expertise to join the team.
What you'll do
Design and build reinforcement learning environments for chemistry end to: end, including task design, data curation, automated grading, and checks against shortcuts and data leakage
Design and source new experimental datasets, environments, and evaluations: with our bench chemists, and external research and academic partners
Develop evaluations that measure model performance on real chemistry tasks,: such as reaction outcome prediction, synthesis planning, structure elucidation, and compound design, and feed results back to research teams
Run and analyze training experiments with AI research teams, diagnose where: models fail at chemistry, and prioritize what to build next
Ensure datasets and environments are high quality and well documented,: including sources, train and test splits, and failure modes
Communicate findings clearly to chemistry, AI research, and life sciences audiences
What they're looking for
- Experience with reinforcement learning, large language models, or building evaluations and benchmarks
- Track record of supporting drug discovery programs alongside medicinal and synthetic chemists
- Experience curating chemistry datasets from the literature, patents, or lab: notebooks, including reaction, ADMET, and spectroscopic data
- Cheminformatics and molecular modeling skills, for example RDKit, docking,: free energy calculations, or quantum chemistry
- Hands-on synthetic or medicinal chemistry experience at the bench
- Publications, patents, or open-source software demonstrating scientific impact
