AI Biologist - Structural Biology
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 Structural Biology team, pushing what AI can achieve in interpreting macromolecular structure.
About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert structural biologist. AI agents today read a deposited model as fact. They miss that a ligand sits in empty density, that the two chains in a crystal file are a packing contact rather than the biological dimer, that a confident AlphaFold prediction shows the wrong conformational state, or that a stretch of chain is built out of register. Separating what the data actually support from what the model asserts is the core of the job. Knowing where the evidence ends, and when a structure cannot support a claim, is part of the work.
The role is intentionally broad, spanning molecular systems, experimental and computational methods, and questions from structure determination to interaction analysis, molecular dynamics, and functional interpretation. You will work with software engineers and scientists to build benchmark tasks and datasets across viral and bacterial proteins, toxins, RNA elements, and host–pathogen complexes. Your judgment will set the standard for agent outputs across these areas, including:
Build the Task
Define what expert reasoning looks like for a structural question, and write gold-standard answers with the rationale an experienced crystallographer, cryo-EM scientist or biophysicist would defend.
Design realistic scenarios across the structural workflow: data collection and processing, map interpretation, model building, validation, assembly and state assignment, comparison, functional interpretation, protein–protein interaction analysis, molecular dynamics simulation, and metadynamics.
Curate datasets across modalities: X-ray structure factors and maps, cryo-EM maps and half-maps, atomic models, AlphaFold predictions with confidence metrics, molecular dynamics and metadynamics simulations and trajectories, NMR shifts and ensembles, SAXS curves, HDX-MS, cross-linking, and SHAPE/DMS reactivity.
Build analysis pipelines in Python (gemmi, Biopython/biotite, numpy) that compute verifiable ground truth directly from the files the agent receives.
Partner with software engineers to turn your judgment into new workflows.
Set the hard tasks
Test whether agents distinguish real structure from artifact or over-interpretation: unsupported ligands, register shifts, mirrored maps, crystal contacts read as interfaces, misdocked domains, and B-factors or occupancies treated as evidence.
Adjudicate ambiguous cases: decide what the map or measurement supports, where reasonable experts would disagree, and which additional data, such as a higher-resolution class, a solution-state measurement or a mutant, would settle the call.
Test whether agents choose the right representation and comparison for the question: the biological assembly versus the asymmetric unit, the right reference state, and which domain to superpose on.
Judge the agent
Interrogate agent reasoning step by step, and challenge conclusions that sound right but would not survive peer review or a validation report.
Pinpoint where agents go wrong: why a step fails, what an expert would do instead, and what evidence would change the call.
Score agent confidence, rewarding explicit uncertainty over overconfident calls on ambiguous structures.
Requirements
PhD in structural biology, biophysics, biochemistry, or a related field.
Hands-on structural experience: you have built and validated models yourself, and you know what a good and a bad map, model and fit look like.
Deep expertise in at least one area (X-ray crystallography, cryo-EM, NMR/solution methods, or computational structural biology) and working fluency across the others.
Coding for structural data: you can compute contacts, superpositions, symmetry mates, map values and geometry from files without a GUI.
AI-ready from day one: daily use of Claude, Cursor, or similar agents, with the judgment to spot where model reasoning is technically correct but scientifically unsound.
Confidence to overrule an AI agent when the evidence demands it, and the openness to update when shown wrong.
Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary calls.
Bonus: structural virology or antibody–antigen structural work (viral glycoproteins, epitope mapping, structural interpretation of escape)
Bonus: RNA structural biology, protein–RNA interaction analysis
Culture @ Latch
How we work. 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 respectfully opinionated, we respect each other’s time, and we think through possible solutions before we bring a problem to anyone. Most of the team arrives between 7 and 10am and leaves between 4 and 7pm. Nobody tracks when you’re in, but we give each other a heads-up on Slack when we’re running later than usual. We judge output, not time in a seat, and the only fixed meeting are a few pod check-ins per week. 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 offsites, and a community that does cycling, soccer, figure skating, boxing, running, martial arts, music, books, and game nights.
Compensation & Logistics (US)
Pay: $140K–$180K OTE, a mix of base & uncapped performance pay. Split varies by state.
Performance pay is based on weekly quota attainment.
If we pull you onto a special project, you’re paid full OTE for its duration.
If the platform goes down, you’re paid full OTE for that day.
Ramp: full OTE for your first 4 weeks while we onboard you into our workflows.
Employment: full-time W-2
Health, dental, vision: 100% covered for you, 50% for dependents
401(k) (no match)
PTO: 12 days to start, more as you’re promoted
Growth: promotions are based on output, not tenure, with OTE rising at each level.
Location: remote, hybrid, or onsite in SF. Onsite is preferred: waterfront office in Mission Bay, catered lunch and dinner, unlimited snacks.
Work authorization: we sponsor H-1B (incl. transfers), O-1, TN, and support STEM OPT.
Interview Process
Timeline: We move fast: no longer than 2 week interview process
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