AI Biologist - Drug Development

The role

You will contribute to the technical approach for evaluating agent performance across the drug discovery and development pipeline. You will work with software engineers and scientists to build datasets and AI agent tasks.

What you will do

• Designing realistic program case studies across modalities
• Curating multi-modal preclinical data bundles
• Evaluating PK/PD, GLP toxicology, and safety pharmacology findings
• Reconstructing program go/no-go decisions from multi-source data
• Reviewing and stress-testing agent outputs for pharmacological soundness
• Calibrating AI agent confidence on preclinical data

Required qualifications

• Advanced degree (MS/PhD/PharmD) in pharmacology, toxicology, pharmaceutical sciences, medicinal chemistry, or a related biomedical field, or equivalent industry experience
• 3+ years of hands-on experience in pharma or biotech drug discovery/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/tox study types: GLP tox, safety pharmacology, genotoxicity, biodistribution, bioanalytical assays
• Experience evaluating SAR, potency, selectivity, and developability trade-offs across candidate molecules
• Strong scientific writing skills
• Proficiency in AI agent use
• Comfort operating in uncertainty
• Works with high agency and initiative

Nice to have

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

Benefits

• Health, dental, vision: 100% covered for you, 50% for dependents
• 401(k) (no match)
• PTO: 12 days to start, more as you’re promoted
• Catered lunch and dinner (onsite)
• Unlimited snacks (onsite)

Before you apply

• If your profile matches, we’ll send you a take-home project
• Background check, once you accept

About the company

Latch builds rigorous scientific benchmarks for AI agents across biology. They work with frontier labs and pharma to measure whether agents can handle real biological workflows.