# AI Biologist - Longevity at LatchBio

LatchBio is hiring an AI Biologist - Longevity in San Francisco, United States. It pays $140k-$180k a year and Level rates it Builds AI ●●●●; you can [apply on LatchBio](https://jobsbylevel.com/go/a3ad93f3-8cdc-49cd-a989-6b6120e2ec75?utm_medium=ai-agent).

AI Level 4, AI centrality 86 out of 100. San Francisco (preferred).

## Details

- Company: [LatchBio](https://jobsbylevel.com/companies/latchbio)
- AI level: AI Level 4 (score 86 out of 100)
- Location: San Francisco (preferred)
- Salary: $140k-$180k
- Posted: November 10, 2026
- Apply: https://jobsbylevel.com/go/a3ad93f3-8cdc-49cd-a989-6b6120e2ec75?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=ai-biologist-longevity-at-latchbio-ac02ec

## Prepare for this job

The job page lists 3 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/ai-biologist-longevity-at-latchbio-ac02ec

## Description

AI Biologist - Longevity 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 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

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