Staff Machine Learning Scientist at Freenome
Brisbane, CA
$199,675–$283,500from the description
Jul 15, 2026
Brisbane, CA
Jul 21, 2026
What this job asks for AI summary
This role centers on developing machine learning and deep learning models for blood-based early cancer detection, working within a computational science team. Day-to-day work involves building and refining models that extract molecular signals from blood, applying interpretability techniques to surface potential biological mechanisms, and collaborating with computational biologists and ML engineers. It suits a research-oriented ML scientist with a strong publication or industry track record and at least six years of post-PhD experience.
Staff level · 6+ years · Remote · Doctorate required · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 520 people nationally plausibly meet what this posting asks for (data scientists). range 110–940
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
The degree requirement is PhD or 'equivalent research experience' — because the JD accepts equivalent experience in lieu of a formal doctorate, the degree requirement is set to None per schema rules; however, the PhD framing is the primary gate and the equivalence qualifier is narrow ('equivalent research experience with an AI emphasis'), so this is a borderline call.
The 6+ years figure refers specifically to post-PhD or postdoc industry experience, not total career years — it is treated as the role-level experience minimum.
The role is listed as hybrid (Brisbane, CA HQ, 2–3 days/week) OR fully remote; remote is set to true to reflect that fully remote candidates are explicitly invited.
Brisbane, CA falls within the San Francisco-Oakland-Berkeley, CA CBSA (41860).
The alt SOC (15-1252 Software Developers) is noted because the role involves building and shipping ML models in code, but the primary day-to-day work is research-oriented ML science, making 15-2051 the stronger fit.
Supervised/self-supervised/contrastive learning are listed as training paradigms under Must Haves; they are captured as skills because the JD explicitly gates on 'extensive experience' with each named paradigm.
Computational biology domain experience and genomics/proteomics appear only under 'Nice to haves' and are marked preferred accordingly.
This posting reads as a fully-remote role, so it was scored against the national candidate pool rather than a single metro.
Read the full posting
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