AI Biologist - Longevity
- Location
- San Francisco (preferred)
- Work mode
- On-site
- Employment type
- Full-time
- Salary
- $1,40,000 – $1,80,000 / year
About the job
AI Biologist - Longevity
Latch builds rigorous scientific benchmarks (benchmarks.bio http://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 Longevity team, pushing what AI can achieve in aging biology.
About the Role. You will be the scientific authority on ground truth, testing whether AI agents can reason like an expert aging biologist. Today’s agents struggle to separate biological age from chronological age, spot confounds that make aging signals look real, and judge which longevity claims hold up. Working with real published and public datasets, you’ll build the tasks behind our benchmarks, starting with aging biomarkers and the hallmarks of aging. Your judgment sets the standard agents are held to.
Build the task
- Turn real aging research questions into tasks, and write gold-standard answers an expert would defend
- Curate data across molecular and population scales: DNA methylation, transcriptomics, proteomics, single-cell, longitudinal cohorts and biobanks
- Build tasks around aging clocks, biological age prediction, senescence, epigenetic drift, and mitochondrial dysfunction
- Partner with software engineers to turn your judgment into workflows
Set the hard calls
- Test whether agents catch cell-type composition, batch effects, and age imbalance between groups
- Test whether agents know when findings in worms, mice, or cell models won’t translate to human aging
- Adjudicate contested longevity claims: what the data support, what they don’t, and what would settle it
Judge the agent
- Challenge reasoning that sounds right but wouldn’t survive peer review or a go/no-go decision
- Pinpoint where agents fail, what an expert would do instead, and what evidence would change the call
- Reward calibrated uncertainty over confident guesses
Requirements
- Master’s or PhD in biology, bioinformatics, computational biology, or a related field
- Research in aging biology, or in a field where aging is studied: cancer biology, epigenetics, immunology, metabolism, mitochondrial biology, neurodegeneration, or epidemiology
- Working knowledge of aging: the hallmarks, how clocks are built, and biological vs. chronological age
- Depth in at least one of:
- Computational: machine learning or statistics on omics data
- Experimental: hands-on experience generating omics or aging data (sequencing, model organisms, senescence or mitochondrial assays), so you know how experiments go wrong
- You code your own analysis end to end in Python or R
- Work you drove yourself (first-author paper, thesis, independent project) that you can defend in detail
- A track record of catching errors in data that others missed
- Daily use of AI coding tools, and the confidence to overrule an AI when the evidence demands it
Strongly preferred
- Published research in aging, geroscience, or longevity
- Experience building or validating aging clocks, or analyzing lifespan or healthspan data
- Familiarity with UK Biobank, TCGA, GEO, Tabula Muris Senis, or the NIA Interventions Testing Program
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.
From LatchBio's careers page (Ashby), checked 10 Nov 2026.
How to apply
- Select Apply on latch.bio. It opens LatchBio's own application form in a new tab, run on Ashby.
- Fill in the form and upload your résumé there. Jobiwork never sees your application.
- LatchBio will reply to you directly. No real employer asks you for money to apply.
Posted 10 Nov 2026 · checked 10 Nov 2026 · Report this job