AI Biologist - Drug Development

LatchBio • San Francisco, CA

7d

About The Position

Latch builds scientific benchmarks for AI agents across biology and works with frontier labs and pharmaceutical companies to assess agents on real biological workflows. The AI Biologist - Drug Development will help develop methods for evaluating agent reasoning across the drug discovery and development pipeline, from target validation through IND-enabling studies, including how preclinical data informs decisions to advance or discontinue a program.

The role works with software engineers and scientists to build datasets and AI-agent tasks spanning drug development. Work includes creating realistic program case studies, curating multimodal preclinical data, evaluating pharmacology and safety findings, reconstructing program decisions from multiple sources, and reviewing agent outputs for scientific and practical soundness. The role also assesses how agents express confidence when preclinical data is incomplete or conflicting.

Latch describes a culture of radical transparency, collaborative problem-solving, and judging output rather than time in a seat. Team members typically arrive between 7 and 10 a.m. and leave between 4 and 7 p.m.; schedules are not tracked, and employees give colleagues a heads-up on Slack when running later than usual. The role begins on the team bench that fits the employee’s expertise, with opportunities to move across teams as they build a track record.

The position is full-time W-2 and may be remote, hybrid, or onsite in San Francisco; onsite work is preferred. Compensation is $140,000–$180,000 OTE, comprising base pay and uncapped performance pay, with the split varying by state. Performance pay is based on weekly quota attainment. Full OTE is paid during the first four weeks of onboarding, for the duration of special projects, and on days when the platform is down. Benefits include health, dental, and vision coverage fully covered for the employee and 50% covered for dependents, a 401(k) with no match, and 12 days of PTO to start, with more as employees are promoted. The company also offers equity, with promotions and OTE increases based on output rather than tenure. The San Francisco office is on the waterfront in Mission Bay and provides catered lunch and dinner and unlimited snacks. Latch sponsors H-1B visas, including transfers, O-1 and TN visas, and supports STEM OPT.

Requirements

• Advanced degree (MS, PhD, or PharmD) in pharmacology, toxicology, pharmaceutical sciences, medicinal chemistry, or a related biomedical field, or equivalent industry experience.
• At least 3 years of hands-on experience in pharma or biotech drug discovery or development.
• Direct experience with lead optimization, candidate nomination, or IND-enabling study design in at least one modality.
• Experience interpreting PK/PD, ADME, and GLP toxicology data to inform dose selection and risk assessment.
• Working knowledge of core pharmacology and toxicology study types, including GLP toxicology, safety pharmacology, genotoxicity, biodistribution, and bioanalytical assays.
• Experience evaluating SAR, potency, selectivity, and developability trade-offs across candidate molecules.
• Strong scientific writing skills and ability to produce clear, evidence-supported rationales for drug development decisions.
• Proficiency in using AI agents and judgment to identify model reasoning that is technically correct but pharmacologically or practically unsound.
• Comfort operating amid uncertainty and proactively flagging gaps in data or instructions.
• High agency and initiative.

Nice To Haves

• Familiarity with IND-enabling regulatory requirements and the nonclinical data package expected by the FDA and EMA.

Responsibilities

• Contribute to the technical approach for evaluating AI-agent reasoning across the drug discovery and development pipeline, from target validation through IND-enabling studies.
• Design realistic program case studies spanning target validation, lead optimization, candidate nomination, and IND-enabling studies across modalities.
• Curate multimodal preclinical data bundles, including SAR and potency panels, ADME/PK profiles, in vivo efficacy, GLP toxicology, safety pharmacology, and biodistribution data.
• Evaluate PK/PD, GLP toxicology, and safety pharmacology findings across modalities and development stages.
• Reconstruct program go/no-go decisions from multiple data sources.
• Review and stress-test agent outputs for pharmacological soundness, identifying reasoning that may be textbook-correct but not defensible in a program review.
• Calibrate AI-agent confidence on preclinical data with incomplete or conflicting signals rather than forcing binary conclusions.
• Work with software engineers and scientists to build datasets and AI-agent tasks across the end-to-end drug development pipeline.
• Proactively identify gaps in data or instructions and provide clear, evidence-supported rationales for drug development decisions.

Benefits

• Health, dental, and vision coverage fully covered for the employee and 50% covered for dependents.
• 401(k) plan with no match.
• 12 days of PTO to start, with more as employees are promoted.
• Equity.
• OTE increases with promotion.
• Catered lunch and dinner and unlimited snacks at the San Francisco office.
• Visa sponsorship for H-1B, including transfers, O-1, and TN; support for STEM OPT.

What This Job Offers

• Job Type: Full-time