Machine Learning Engineer (Staff)
Sprinter Health · San Francisco, CA
$220,000–$270,000
Jul 19, 2026
San Francisco, CA
Jul 21, 2026
What this job asks for AI summary
This is a founding ML engineering role responsible for building the infrastructure that takes machine learning models from prototype to production — covering training and inference pipelines, feature workflows, model serving, monitoring, drift detection, and retraining automation. The position also sets architectural and governance standards that future engineers will inherit. It suits a hands-on, senior engineer with a strong background in production ML systems who is comfortable making long-lived platform decisions in an early-stage environment.
Staff level · 8+ years · Remote · Full-time
“or” means any one of them counts — you don't need all of them.
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 820 people nationally plausibly meet what this posting asks for (computer occupations, all other). range 240–1,200
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 $119,144 (middle half $81,115–$160,963).
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 caller has declared this a fully-remote role; the posting itself describes a Bay Area hybrid schedule (Mon–Thu in-office in San Francisco or Menlo Park), so remote=true overrides the JD's stated location and no metro has been set.
SOC 15-1299 (Computer Occupations, All Other) is used because this is a founding ML Engineering / MLOps platform role — primarily building production ML infrastructure — which sits between Software Developers (15-1252) and Data Scientists (15-2051); 15-2051 is the runner-up given the ML modeling context.
Seniority is set to Staff, matching both the advertised title and the genuine scope: org-wide, first-of-function, cross-team technical authority with architectural decision rights — not merely a senior IC.
The 8+ years figure is stated at the role level ('8+ years building production software, data systems, ML systems…') and is captured as the overall years minimum; no per-technology year counts are given.
LLMs, feature stores, real-time inference, and HIPAA experience appear only under the 'What gives you an edge' section (explicitly framed as differentiators, not gates) and are marked preferred accordingly.
No compensation figures are disclosed in the posting.
Ignored 3 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML model training pipelines, ML model serving / inference pipelines, model governance.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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