Greenhouse ·
full-timeResearch Scientist, Life Sciences (computational Chemistry)
Anthropic · San Francisco, CA
Anthropic is an AI research company focused on building reliable, interpretable, and steerable AI systems. The Life Sciences team is currently seeking a Research Scientist to bridge the gap between computational chemistry and machine learning. In this role, you will be responsible for developing reinforcement learning environments and datasets specifically designed to teach chemistry to AI models. Your day-to-day tasks will involve designing evaluation frameworks, sourcing experimental data in collaboration with bench chemists, and running training experiments to measure model performance on complex tasks like synthesis planning and structure elucidation. You will diagnose model failures, curate high-quality datasets, and communicate technical findings to cross-functional research teams. This position is ideal for a candidate with a PhD in chemistry or a related field who possesses both deep domain expertise in organic and medicinal chemistry and strong proficiency in Python and machine learning. The role requires someone comfortable navigating ambiguity and capable of translating real-world chemistry problems into effective training tasks for AI systems. This is a fully on-site position based in the San Francisco Bay Area.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role 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. 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 a computational chemist who knows reactions, synthesis, and medicinal chemistry in depth and has hands-on experience training and evaluating machine learning models. Above all, you'll build the reinforcement learning environments, datasets, and evaluations that teach Claude chemistry. Working alongside our bench chemists and AI researchers, you'll turn real chemistry problems and experimental data into training tasks and measure whether the models get better at them. This role is fully on-site in the San Francisco Bay Area. Key responsibilities 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 Minimum qualifications PhD in chemistry, computational chemistry, or a related field Deep knowledge of organic and medicinal chemistry, including reactions, synthesis, and SAR, with experimental data as your 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 while collaborating effectively across cross-functional teams, with strong written and verbal communication skills Preferred qualifications 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 The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems lik
| Role | Research Scientist, Life Sciences (computational Chemistry) |
|---|---|
| Company | Anthropic |
| Location | San Francisco, CA |
| Type | full-time |
| Compensation | Not disclosed |
| Posted | 2026-10-25 |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4Research Scientist, Life Sciences (computational Chemistry) at Anthropic: frequently asked questions
- What is the salary for this role?
- Anthropic has not stated compensation in the listing. Check the original posting or ask during the application process.
- Is the Research Scientist, Life Sciences (computational Chemistry) position remote, hybrid or onsite?
- The listing gives San Francisco, CA as the location and does not state a work mode.
- What is the application deadline?
- Anthropic has not listed a fixed deadline, so apply early in case the opening is filled.
- How do I apply for the Research Scientist, Life Sciences (computational Chemistry) role?
- Use the Apply button on this page. It opens the original listing on job-boards.greenhouse.io, where you submit your application with the company.
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