Research Scientist, Life Sciences (Chemistry)

Anthropic•San Francisco, CA

3h•$300,000 - $320,000•Onsite

About The Position

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 research scientists with deep medicinal chemistry expertise to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be an expert medicinal chemist with hands-on experience designing, synthesizing, purifying, and characterizing small molecules. Above all, you'll close the loop between AI-generated hypotheses and experimental data to share with the community. Working alongside AI researchers and engineers, you'll drive experimental programs end to end and pressure-test AI-designed molecules and AI-proposed synthetic routes against real chemistry. This role is fully on-site in the San Francisco Bay Area.

Requirements

PhD in chemistry
Demonstrated medicinal chemistry experience, including SAR-driven design and optimization of small molecules, with recent, sustained hands-on synthetic work
Comfort navigating ambiguity and defining problems in a rapidly evolving research environment
Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills

Nice To Haves

5+ years of medicinal chemistry experience beyond the PhD
Track record of advancing programs from hit identification through lead optimization
Experience directing synthetic chemistry activities at contract research organizations
Computational chemistry, cheminformatics, or coding skills, for example Python with RDKit or pandas for data analysis and automation
Experience using AI or ML tools in the life sciences
Publications and/or patents demonstrating scientific impact

Responsibilities

Design multi-step synthetic routes for small molecules and oversee their execution end to end, including route selection, reaction optimization, purification strategy, and interpretation of full characterization data (NMR, LC-MS, HPLC)
Coordinate synthesis and biological evaluation with external contract research organizations and academic partners
Evaluate AI-designed molecules and AI-proposed synthetic routes, drive them to experimental readout, and feed results back to research teams
Apply medicinal chemistry principles, including SAR analysis and physicochemical property optimization, to compound design and prioritization
Ensure experimental data across programs is high quality and well documented, including procedures, spectra, and failure modes
Communicate findings clearly to chemistry, AI research, and life sciences audiences