AI Biologist - Pathogen Countermeasures
$140K to $180K a year
AI Biologist - Pathogen Countermeasures
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 to join our Pathogen Countermeasures team, pushing what AI can achieve in vaccine, antibody, and antiviral development against respiratory viruses.
About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert countermeasures scientist. The benchmark covers vaccines, therapeutic antibodies, and antivirals for influenza, RSV, and coronaviruses. AI agents today struggle to interpret raw neutralization, epitope, and drug-response data, to separate real escape or resistance from assay noise, and to make the advance-or-kill calls an expert would stand behind. You’ll work with scientists and engineers to build the tasks and datasets behind our benchmarks, and your judgment will set the standard agent outputs are held to.
Build the task
Turn real countermeasure workflows into tasks with clear, gradable answers: antigen and immunogen comparison, epitope mapping, neutralization and cross-reactivity, antiviral susceptibility, and resistance interpretation
Write gold-standard answers from raw data, with tolerances that reflect real assay, replicate, and strain variability
Curate data: neutralization titers, binding and epitope maps, serology time courses, EC50 and dose-response curves, and viral sequences with resistance markers
Set the hard calls
Test whether agents can tell real escape or resistance from artifact: a titer drop that’s really assay drift, a passenger mutation mistaken for a resistance marker, or a single fold-change not backed by sequence data
Test whether agents separate binding from neutralization, immunogenicity from protection, and lab resistance from clinical relevance
Test whether agents account for immune imprinting, waning, and cross-resistance when ranking candidates
Judge the agent
Challenge conclusions that sound right but wouldn’t survive a program 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
3+ years of hands-on experience in either vaccine/antibody development or antiviral development, ideally in respiratory viruses (influenza, RSV, or coronaviruses)
Deep expertise in at least one of the areas below, in priority order within each track: Vaccines and antibodies
Vaccine antigen design, immunogen engineering, or therapeutic antibody discovery
Epitope mapping, neutralization, cross-reactivity, and immune recognition
Comparative evaluation of vaccine or antibody candidates from experimental data
Antibody responses, immune imprinting, or waning immunity
Antivirals
Antiviral susceptibility and resistance, including phenotypic drug-response and viral sequence data
Antiviral discovery, mechanism-of-action studies, or experimental evaluation of candidates
Treatment-emergent resistance, cross-resistance, and resistance-marker interpretation
Antiviral assay development, validation, and dose-response analysis
PhD in immunology, virology, microbiology, or a related field, or equivalent industry experience
You’ve analyzed the data yourself, not just supervised it
AI-ready: daily use of Claude, ChatGPT, or similar, with the judgment to spot answers that are technically correct but scientifically wrong
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.