Research Scientist, Life Sciences (Computational Chemistry)

Location: Fully on-site in the San Francisco Bay Area, with staff expected to be in an Anthropic office at least 25% of the time; this role may require more office time.

Salary: $300,000–$320,000 USD annual salary.

Company

Anthropic builds reliable, interpretable, and steerable AI systems and conducts large-scale AI research focused on beneficial and safe AI.

What you will do

• Design and build reinforcement learning environments for chemistry, including task design, data curation, automated grading, and checks for shortcuts and data leakage.
• Design and source experimental datasets, environments, and evaluations with bench chemists, external research partners, and academic partners.
• Develop evaluations for reaction outcome prediction, synthesis planning, structure elucidation, and compound design, and feed results back to research teams.
• Run and analyze training experiments, diagnose chemistry-related model failures, and prioritize future research and development.
• Ensure datasets and environments are high quality and well documented, including sources, train and test splits, and failure modes.
• Communicate findings to chemistry, AI research, and life sciences audiences.

Requirements

• PhD in chemistry, computational chemistry, or a related field.
• Deep knowledge of organic and medicinal chemistry, including reactions, synthesis, and SAR, using experimental data as ground truth.
• Strong Python skills and solid machine learning fundamentals, with hands-on experience training and evaluating models.
• Comfort navigating ambiguity and defining problems in a rapidly evolving research environment.
• Ability to work independently and collaborate effectively across cross-functional teams, with strong written and verbal communication skills.
• Minimum education is a bachelor's degree or equivalent combination of education, training, and/or experience; the required field of study must be relevant to the role through coursework, training, or professional experience. Years of experience correlate with internal job-level requirements.

Nice to have

• Experience with reinforcement learning, large language models, or building evaluations and benchmarks.
• Track record supporting drug discovery programs alongside medicinal and synthetic chemists.
• Experience curating chemistry datasets from literature, patents, or lab notebooks, including reaction, ADMET, and spectroscopic data.
• Cheminformatics and molecular modeling skills, such as 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.

Culture & Benefits

• Collaborative research environment organized around a small number of large-scale research efforts.
• Frequent research discussions and emphasis on high-impact, empirical AI research.
• Competitive compensation, optional equity donation matching, generous vacation and parental leave, flexible working hours, and an office space for collaboration.
• Visa sponsorship may be available, with reasonable efforts and immigration-lawyer support for eligible offers; sponsorship is not guaranteed for every role or candidate.