AI Biologist - Proteomics

About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert mass spectrometrist. AI agents today struggle to interrogate raw mass spec data, separate real biological signal from artifacts of sample prep, instrument behavior, and processing, and reach conclusions an expert would stand behind. You will work with software engineers and scientists to build the tasks and datasets behind our proteomics benchmarks, and over time lipidomics and metabolomics. Your judgment will set the standard agent outputs are held to, including:

Build the task

* Define what expert reasoning looks like for a mass spec question, and write gold-standard answers with the rationale an experienced mass spectrometrist would defend

* Design realistic scenarios across the workflow: sample prep, acquisition, identification, quantification, and biological interpretation

* Curate mass spec datasets across proteomics, lipidomics, and metabolomics, alongside antibody-based and sequencing data where relevant

* Partner with software engineers to turn your judgment into new workflows

Set the hard calls

* Test whether agents can tell true biological signal from batch effects, contamination, poor identifications, or processing artifacts

* Adjudicate ambiguous results: decide what the data supports, what it doesn’t, and which experiment would settle the question

Judge the agent

* Interrogate agent reasoning step by step, and challenge conclusions that sound right but wouldn’t survive lab meeting or peer review

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

* Score agent confidence, rewarding explicit uncertainty over overconfident calls

Requirements

* PhD in proteomics, analytical chemistry, biochemistry, or a related field

* Hands-on mass spectrometry experience with first-hand data analysis and a publication record

* Mass spec experience beyond proteomics alone: lipidomics or metabolomics strongly preferred

* Strong command of experimental design and statistics

* 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

* Bonus: protein sequencing or antibody experience

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

1. Apply. If your profile matches, we’ll send you a take-home project.

2. Take-home project (HackerRank). We review it as soon as it arrives.

3. Technical interview with a Member of Technical Staff (pod lead), scheduled right after your project review.

4. Culture interview with our C-suite.

5. Offer.

6. Background check, once you accept.