AI Biologist - Genetic Medicines

latch.bio; San Francisco (CA); Remote; USD 140,000 - 180,000; Full time

Benefits offered by this job

Health, dental, vision

401(k) with no match

PTO: 12 days to start

Job summary

Latch.bio seeks an AI Biologist to advance evaluation of AI agents in genetic medicines, covering gene therapy, gene editing, and RNA therapeutics from discovery to clinical development.

You will work with software engineers and scientists to build datasets and AI agent tasks across the end-to-end pipeline, including designing case studies, evaluating data, and ensuring scientific soundness of model outputs.

Qualifications

• Advanced degree in a biomedical field or equivalent industry experience.
• 3+ years in gene therapy, gene editing, or RNA therapeutics discovery or development.
• Experience interpreting on-/off-target editing data, biodistribution, immunogenicity, and GLP toxicology.

Responsibilities

• Design realistic program case studies across target validation, drug design, and screening in genetic medicines.
• Evaluate PK/PD, immunogenicity, and GLP toxicology findings to inform dose selection and risk.
• Reconstruct go/no-go decisions from multi-source data.
• Review and stress-test AI agent outputs for scientific soundness.
• Calibrate AI agent confidence with incomplete or conflicting data.

Skills

Scientific writing

Independent work

Data interpretation

Critical thinking

Team collaboration

Adaptability

Education

MS/PhD/PharmD in molecular biology, genetics, gene therapy

Tools

AI agent tools

Job description

AI Biologist - Genetic Medicines

Latch builds rigorous scientific benchmarks (benchmarks.bio http://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

1. Take-home project (HackerRank). We review it as soon as it arrives.
2. Technical interview with a Member of Technical Staff (pod lead), scheduled right after your project review.
3. Culture interview with our C-suite.
4. Offer.
5. Background check, once you accept.