AI Biologist - Immunology

AI Biologist - Immunology

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 are seeking an AI Biologist to join and help build our Immunology team, working at the frontier of what agents can achieve in biology.

About the Role

You will contribute to our technical approach for evaluating how AI agents reason about immunology. Working with software engineers and computational biologists, you'll build ground-truth benchmark datasets, drawn from studies, your experience, and novel work, that rigorously test whether agents can perform the critical analytical and interpretive steps that expert immunologists do.

Requirements

• Master's or PhD in Immunology, Cell Biology, Bioengineering, or related field

• 3+ years of hands-on research experience in relevant domains, with impact demonstrated through publications or industry experience

• Proficiency in Python and/or R for biological data analysis and visualization OR expert-level experience in experimental or methods design

• Deep experience in at least one of the following: basic immune cell biology, immune signaling, vaccine development, autoimmunity, cancer immunology, infectious disease/host defense, immune cell therapies, or any other immunology subdomain you believe LLMs reason poorly about

Build the task

• Turn real immunology workflows into tasks with clear answers: immune profiling, vaccine immunogenicity, T and B cell responses, inflammation and autoimmunity readouts, and immune cell engineering

• Write gold-standard answers from raw data, with tolerances that reflect real donor, assay, and gating variability

• Curate data: flow and spectral cytometry, single-cell and CITE-seq, TCR/BCR repertoires, cytokine panels, serology and neutralization titers, ELISpot

Set the hard calls

• Test whether agents can tell real biology from artifact: a doublet or spillover “population,” a batch effect, a clonal expansion that’s really sampling depth

• Test whether agents separate immunogenicity from protection, activation from exhaustion, and mouse findings from human relevance

Judge the agent

• Challenge conclusions that sound right but wouldn’t survive expert review

• Pinpoint where agents go wrong, what an expert would do instead, and what evidence would change the call

• Reward explicit uncertainty over confident guesses

Requirements

• PhD in immunology, vaccinology, or a related field

• Deep expertise in at least one: vaccine development, T/B cell or innate immune biology, autoimmunity, cancer immunology, inflammation, or immune cell engineering, shown through peer-reviewed work or industry programs

• You’ve analyzed immune data yourself (FlowJo, R, Python, or similar). You don’t need to be a programmer

• Industry experience preferred

• Use of Claude, ChatGPT, or similar, with the judgment to spot answers that are technically correct but scientifically wrong

• Strong domain confidence to overrule an AI agent, and openness to update when shown wrong

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.