Research Scientist, Life Sciences (Computational Chemistry)

Description

The Life Sciences team is forming a research group that pairs AI with hands-on biology to make new discoveries. The aim is to speed up life sciences progress by an order of magnitude.

You will be a computational chemist with deep knowledge of reactions, synthesis and medicinal chemistry, plus practical experience training and testing machine learning models. Your central task is building reinforcement learning environments, datasets and evaluations that help Claude learn chemistry.

You will work with bench chemists and AI researchers to convert real chemistry problems and lab data into training tasks, then measure whether the models improve.

The company builds AI systems that are reliable, interpretable and steerable. The team is small and growing, made up of researchers, engineers, policy experts and business leaders, and works on a few large research efforts with a strong emphasis on clear communication.

The role is fully on-site in the San Francisco Bay Area.

Responsibilities

• Build reinforcement learning environments for chemistry from start to finish, covering task design, data curation, automated grading, and guards against shortcuts and data leakage
• Find and design new experimental datasets, environments and evaluations together with bench chemists and external research and academic partners
• Create evaluations that test model performance on practical chemistry work such as reaction outcome prediction, synthesis planning, structure elucidation and compound design, and pass the results to research teams
• Run and review training experiments with AI research teams, pinpoint where models struggle with chemistry, and decide what to build next
• Make sure datasets and environments are high quality and thoroughly documented, including their sources, train and test splits and known failure modes
• Explain findings clearly to chemistry, AI research and life sciences audiences

Requirements

• Minimum: a PhD in chemistry, computational chemistry or a related field
• Minimum: deep knowledge of organic and medicinal chemistry, including reactions, synthesis and SAR, with experimental data as the reference point
• Minimum: strong Python skills and solid machine learning fundamentals, with hands-on experience training and evaluating models
• Minimum: comfort working through ambiguity and defining problems in a fast-changing research setting
• Minimum: ability to work independently while collaborating well across teams, with strong written and verbal communication
• Minimum education: a Bachelor's degree or an equivalent mix of education, training and experience
• Required field of study: a field relevant to the role, shown through coursework, training or professional experience
• Minimum years of experience: set by the internal job level for the position
• Preferred: experience with reinforcement learning, large language models, or building evaluations and benchmarks
• Preferred: a record of supporting drug discovery programs alongside medicinal and synthetic chemists
• Preferred: experience curating chemistry datasets from literature, patents or lab notebooks, including reaction, ADMET and spectroscopic data
• Preferred: cheminformatics and molecular modeling skills, such as RDKit, docking, free energy calculations or quantum chemistry
• Preferred: hands-on synthetic or medicinal chemistry experience at the bench
• Preferred: publications, patents or open-source software that show scientific impact

Conditions

Annual salary range: $300,000 - $320,000 USD

Location-based hybrid policy: staff are currently expected to be in an office at least 25% of the time, though some roles may require more time in the office

Visa sponsorship is available, but not for every role and every candidate; if an offer is made, the company will make every reasonable effort to obtain a visa and retains an immigration lawyer to help

Candidates are encouraged to apply even if they do not meet every listed qualification

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• A well-equipped office space for collaborating with colleagues