[Hiring] AI Biologist - Genetic Medicines @LatchBio

Role Description

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

Qualifications

• 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

Requirements

• 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.
• 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.

Benefits

• 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.