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 - Genetic Medicines to join our team working at the frontier of what artificial intelligence can achieve in gene therapy, gene editing, and RNA therapeutics development.
About the Role
You will contribute to our technical approach for evaluating agent performance at reasoning across the genetic medicines pipeline – gene therapy, gene editing, and RNA therapeutics from target validation and drug discovery to clinical development.
You will work as part of a team of software engineers and scientists building datasets and AI agent tasks across the end-to-end genetic medicines pipeline, including:
Designing realistic program case studies spanning target validation, drug design and screening, chemistry optimization, candidate nomination, and IND-enabling studies across genetic medicine modalities
Evaluating PK/PD, immunogenicity, and GLP toxicology findings across modalities and development stages
Reconstructing program go/no-go decisions from multi-source data
Reviewing and stress-testing agent outputs for scientific 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 molecular biology, genetics, gene therapy, or a related biomedical field, or equivalent industry experience
3+ years of hands-on experience in gene therapy, gene editing, or RNA therapeutics (ASO/siRNA/mRNA) discovery or development
Direct experience with drug design, drug screening, delivery optimization, or IND-enabling study design in at least one genetic medicine modality
Experience interpreting on-/off-target editing data, biodistribution, immunogenicity, and GLP toxicology to inform dose selection and risk assessment
Familiarity with IND-enabling regulatory requirements and the nonclinical data package expected by FDA/EMA is a plus
Experience evaluating potency, specificity, and developability trade-offs across vector, construct, or oligonucleotide candidates
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
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 opinionated but respectful of each other’s time, and we think through possible solutions before bringing a problem to anyone. 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 off-sites, and a community that does cycling, soccer, figure skating, boxing, running, martial arts, music, books, and game nights.
Compensation & Logistics
Pay: $140K–$180K OTE (on-target earnings), with no ceiling.
Your pay is your OTE times your weekly quota attainment. Hit quota, earn your OTE; double it, earn double. Example: $150K OTE at double quota = $300K.
Your first 4 weeks (ramp) are paid at full OTE while we train you.
You’re paid full OTE whenever quota can’t fairly apply: when a new project is starting, the platform goes down, or we pull you onto a special project.
In the US: full-time W-2
Guaranteed base set by your state, paid every paycheck no matter what
Health, dental, vision: 100% covered for you, 50% for dependents
401(k) (no match)
PTO: 12 days to start, more as you’re promoted
Outside the US: contractor
Paid on performance, with a monthly advance of 60% of OTE that’s never clawed back. US benefits don’t apply.
Growth: two tracks, based on output, not tenure.
Individual contributor: six levels, so up to five promotions, with OTE rising at each one.
Management: after your first promotion, you can move into managing a pod if that’s what you want.
Location: fully remote is fine; onsite is preferred, at our Mission Bay waterfront office in SF with catered lunch and dinner and unlimited snacks.
Work authorization: we sponsor H-1B (new and transfers), O-1, and TN, and support STEM OPT.
Interview Process
Apply. If your profile matches, we’ll send you a take-home project.
Take-home project (HackerRank). We review it as soon as it arrives.
Technical interview with a Member of Technical Staff (pod lead), scheduled right after your project review.
Culture interview with our C-suite.
Offer.
Background check, once you accept.