AI Biologist - Structural Biology

LatchBio; San Francisco (CA); Remote; USD 120,000 - 180,000; Full time

Job summary

LatchBio seeks an AI Biologist to join the Structural Biology team, advancing how AI interprets macromolecular structure. You will define gold-standard reasoning and design scenarios across data collection, interpretation, model building, validation, and functional analysis.

Your judgment will set the standard for agent outputs across X-ray, cryo-EM, AlphaFold, and dynamics, while collaborating with software engineers to deploy benchmarks.

Qualifications

• PhD in structural biology, biophysics, biochemistry, or related field.
• Hands-on experience building and validating models.
• Deep expertise in at least one area (X-ray, cryo-EM, NMR, or computational) with fluency across others.
• Coding to compute contacts, superpositions, and map geometry from files.

Responsibilities

• Define expert reasoning for structural questions and write gold-standard answers.
• Design realistic scenarios across structural workflows: data collection, map interpretation, model building, validation, and dynamics.
• Curate datasets across modalities: X-ray, cryo-EM, AlphaFold predictions, MD simulations, NMR, SAXS, etc.
• Build Python analysis pipelines to derive verifiable ground truth from input files.
• Partner with software engineers to turn judgment into new workflows.

Skills

Structural biology

Python scripting

AI judgment

Data interpretation

Education

PhD required

Tools

gemmi

Biopython

crystal analysis tools

Job description

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.

We practice radical transparency: you'll know how the company is doing, what's working, and what isn't. It'll always be us against the problem, never each other. We're opinionated but respectful, and we bring solutions with our problems. You decide how you work; we judge the output. We use AI constantly, so what we reward is 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. People who do well here and bring leadership experience can move quickly into senior roles. Outside of work, we have company outings most months, team off-sites, a Latch run club, cycling, boxing, ice skating, and soccer. Feel free to add to the list.

Compensation & Logistics

• Contract: 1099 (or W-8BEN internationally), no end date.

• Pay: guaranteed for weeks 1-4 while you ramp, then paid per certified task. Most people in this position earn $120K–$180K+ (uncapped upside); certify twice the tasks/week, earn twice the pay that week.

• Commitment: full-time, on your own schedule. Most of the team works 40+ hours a week.

• Meetings: a few pod check-ins a week. The rest of your time is yours.

• Location: remote (anywhere), hybrid, or onsite in SF. We prefer onsite.

• Onsite perks: catered lunch and dinner daily, a waterfront office in Mission Bay, and monthly parking when available.

• Work authorization: US citizens, permanent residents, and OPT holders. We can't support STEM OPT extensions or sponsorship.

Interview Process

We move fast: about 2–3 weeks from your first call, to offer.

1. Intro Screen - Latch Talent Team

2. Take-Home Project - HackerRank

3. Technical Interview - Member of Technical Staff

4. Culture Interview - C-Suite

5. Offer