AI Biologist - Cancer Biology (Applications)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 13d ago
The date the source published, not the day we noticed it (2026-09-01). Last seen at its source 3h ago.
Is it remote?
San Francisco or Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
San Francisco
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $117.5k–130k/yr
Middle 50% of 713 listings that do state pay — Healthcare · all levels · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
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Carried by 1 source
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ashby employer's own board first seen 11d ago · last seen 3h ago
The listing
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.
About the Role
Our work in Cancer Biology means measuring whether an agent can take a tumor case from raw molecular data to a real clinical decision. You'll identify real cancer-biology datasets and turn them into rigorous, deterministically-graded tasks.
Our benchmarks are agentic and cross-domain. Each task hands an agent the artifacts a cancer researcher would actually have and asks for a concrete conclusion. Your job is to establish defensible reference analyses and scoring criteria across conclusion types, the benchmark measures that span basic cancer biology to clinical outcomes. You'll anticipate where agents take plausible but wrong turns and test whether they can handle experimental variability, incomplete data, conflicting evidence, and mechanism-driven tradeoffs.
Our team emphasizes cross-domain integration and long-horizon reasoning.
Requirements
1+ years personally working in basic, translational, or clinical cancer biology. Experience with hands on analysis of multi-omic tumor data hands-on somatic/germline variant calling and interpretation (WES/WGS/panel; MAF/VCF), copy-number and structural-variant analysis, mutational signatures, bulk and single-cell RNA-seq (cell-state annotation, subtyping), tumor-immune contexture (immune deconvolution, spatial transcriptomics, multiplex imaging), subclonal reconstruction, or functional-genomics screens (CRISPR/RNAi), or clinical research is highly preferred.
Proficiency in Python and/or R: VCF/MAF parsing, single-cell analysis (Scanpy/Seurat), gene-set scoring (GSEA/ssGSEA), immune deconvolution (CIBERSORTx), subclonal reconstruction (PyClone), statistical analysis.
Understanding of cancer-genomics standards: AMP/ASCO/CAP and ACMG/AMP variant tiers, ESCAT and OncoKB actionability levels, PAM50 and Consensus Molecular Subtypes, IFN-γ/T-cell-inflamed signature, consensus Immunoscore.
Recognize experimental variability, and assay limitations; distinguish real biological signal from pipeline or annotation artifact.
Strong written communication on technical decisions, uncertainty, and alternative interpretations.
Nice-to-Have
Familiarity with cancer-genomics resources and standards: TCGA/GDC, PCAWG, AACR Project GENIE, cBioPortal, OncoKB/CIViC/VICC, COSMIC signatures, HTAN, Human Cell Atlas, DepMap/Project Score, gnomAD/ClinVar, MSigDB.
Breadth across multiple conclusion types like: diagnosis, mechanism, clonal evolution, immune contexture, target nomination, actionability.
Prior work on benchmarks, task-based assessment, or deterministic grading.
Culture @ Latch
How we work. Genuinely flexible schedules - we just ask that you communicate when you're coming in later than usual. We care most about hard work and output. We're respectfully opinionated, it will always be us against problems, not each other. Optimize for each other's time and bring solutions, not just problems. You'll join a bench suited to your expertise, but we value cross-domain learning and interoperability across teams.
Office & Perks. Waterfront office near Oracle Park, 2x free daily meals, unlimited snacks, company outings most months, and team offsites. Plus a vibrant community: cycling, soccer, figure skating, boxing, run clubs, reading clubs, martial arts, music, game nights.
Compensation & Logistics
1099 (or W8-BEN) contract, 40 hrs/week, no end date
Fully performance-based pay - OTE: $120K–$180K, uncapped upside. 2x quota = 2x pay.
2-4 week paid ramp: full OTE during ramp
Remote (globally), hybrid, or onsite in SF (onsite preferred)
Work authorization: OPT visa holders only (not STEM Extension)
Onsite perks: 2x free meals/day, waterfront office (China Basin), monthly parking (based on availability)
Candidates with all of the above qualifications + proven management skills will be eligible for more senior positions
Interview Process
Timeline: We move fast: 8 - 12 days from submission to offer.
Intro Screen - Technical Recruiter
Take-Home Project - HackerRank
Technical Interview - Member of Technical Staff
Culture Interview - C-Suite
Offer