Research Scientist, Life Sciences (Computational Chemistry)

Job description

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.

For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance

Prepare for the interview

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