AI Biologist - Drug Development
Latch builds rigorous scientific benchmarks (benchmarks.bio) for AI agents across biology. We work with frontier labs and pharma to measure whether agents can handle real biological workflows: the messy, multi-layer reasoning that matters in the field.
We're seeking an AI Biologist - Drug Development to join our team working at the frontier of what artificial intelligence can achieve in drug discovery and development.
About the Role
You will contribute to our technical approach for evaluating agent performance at reasoning across the drug discovery and development pipeline, from target validation through IND-enabling studies, and translating preclinical data into the decisions that advance (or kill) a program.
You will work as part of a team of software engineers and scientists building datasets and AI agent tasks across the end-to-end drug development pipeline, including:
Designing realistic program case studies spanning target validation, lead optimization, candidate nomination, and IND-enabling studies across modalities
Curating multi-modal preclinical data bundles: SAR/potency panels, ADME/PK profiles, in vivo efficacy, GLP toxicology, safety pharmacology, and biodistribution data
Evaluating PK/PD, GLP toxicology, and safety pharmacology findings across modalities and development stages
Reconstructing program go/no-go decisions from multi-source data
Reviewing and stress-testing agent outputs for pharmacological soundness, catching reasoning that is textbook-correct but not defensible in a program review
Calibrating AI agent confidence on preclinical data with incomplete or conflicting signals, rather than forcing a binary call
Requirements
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
Familiarity with IND-enabling regulatory requirements and the nonclinical data package expected by FDA/EMA is s plus
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, able to produce clear, evidence-supported rationale for a drug development decision
Proficiency in AI agent use, with the judgment to identify where model reasoning is technically correct but pharmacologically or practically unsound
Comfort operating in uncertainty, and proactively flagging gaps in data or instructions
Works with high agency and initiative
Culture @ Latch
How we work. We practice radical transparency: you’ll know how the company is doing, what’s working, and what isn’t. It’s always us against the problem, never each other. We’re respectfully opinionated, we respect each other’s time, and we think through possible solutions before we bring a problem to anyone. Most of the team arrives between 7 and 10am and leaves between 4 and 7pm. Nobody tracks when you’re in, but we give each other a heads-up on Slack when we’re running later than usual. We judge output, not time in a seat, and the only fixed meeting are a few pod check-ins per week. We use AI constantly, so we reward original expert judgment, not AI output passed off as your own. You’ll start on the bench that fits your expertise and can move across teams as you build a track record.
Outside of work. Company outings most months, team offsites, and a community that does cycling, soccer, figure skating, boxing, running, martial arts, music, books, and game nights.
Compensation & Logistics (US)
Pay: $140K–$180K OTE, a mix of base & uncapped performance pay. Split varies by state.
Performance pay is based on weekly quota attainment.
If we pull you onto a special project, you’re paid full OTE for its duration.
If the platform goes down, you’re paid full OTE for that day.
Ramp: full OTE for your first 4 weeks while we onboard you into our workflows.
Employment: full-time W-2
Health, dental, vision: 100% covered for you, 50% for dependents
401(k) (no match)
PTO: 12 days to start, more as you’re promoted
Equity
Growth: promotions are based on output, not tenure, with OTE rising at each level.
Location: remote, hybrid, or onsite in SF. Onsite is preferred: waterfront office in Mission Bay, catered lunch and dinner, unlimited snacks.
Work authorization: we sponsor H-1B (incl. transfers), O-1, TN, and support STEM OPT.
Interview Process
Timeline: We move fast: no longer than 2 week interview process
Apply
Take-Home Project - HackerRank
Latch Intro - Talent Team
Technical Interview - Member of Technical Staff
Culture Interview - C-Suite
Offer
Background Check
Advanced degree (MS/PhD/PharmD) in pharmacology, toxicology, pharmaceutical sciences, medicinal chemistry, or related field; 3+ years pharma/biotech drug discovery experience; direct experience with lead optimization, candidate nomination, or IND-enabling studies; proficiency in AI agent use.
Key Responsibilities
- designing case studies
- curating data bundles
- evaluating pharmacology data
Skills & Tools
Slack, HackerRank
Job Details
- Category: Research and Development (R&D)
- Seniority: Mid Level
- Commitment: Full Time
- Workplace: Remote — San Francisco or United States
- Salary: USD 140,000 – 180,000 / year
- Languages: English
Benefits
- Visa sponsorship
- Generous paid time off
- Retirement plan
About LatchBio
A company building rigorous scientific benchmarks for AI agents across biology, working with frontier labs and pharma. — Industry: Information Technology