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LatchBio is seeking an AI Biologist to serve as the scientific authority on ground truth for countermeasures benchmarks. You will assess whether AI agents can reason like expert scientists in vaccines, antibodies, and antivirals for influenza, RSV, and coronaviruses.
You will define tasks, write gold-standard answers, and curate diverse data to calibrate agent performance. You will collaborate with scientists and engineers to convert complex biological workflows into tasks with clear, gradable
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.
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.
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
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
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
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.
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.
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.
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.
fully remote is fine; onsite is preferred, at our Mission Bay waterfront office in SF with catered lunch and dinner and unlimited snacks.
we sponsor H-1B (new and transfers), O-1, and TN, and support STEM OPT.