Applied Scientist, AI at Sprinter Health
San Francisco, CA
$180,000–$260,000
Jul 19, 2026
San Francisco, CA
Jul 21, 2026
What this job asks for AI summary
An applied science role focused on building and deploying machine learning and AI systems for a home-based healthcare company. Day-to-day work spans framing ambiguous clinical and operational problems as modeling tasks, developing solutions across traditional ML, NLP, and LLM approaches, designing rigorous evaluations, and partnering with engineering and clinical stakeholders to move models into production. Best suited to a scientist-engineer comfortable with messy real-world data and high-stakes outcomes.
Senior level · 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 1,650 people nationally plausibly meet what this posting asks for (data scientists). range 690–2,450
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).
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 (9)
The job title is 'Applied Scientist, AI' with no seniority level in the title; the title states no level. However, the scope — end-to-end ownership of modeling problems, production handoff, stakeholder partnership, and clinical collaboration — supports a Senior classification.
No explicit total years of experience are stated anywhere in the posting.
The posting lists Python and a set of ML/AI libraries (PyTorch, scikit-learn, NumPy, pandas, Polars, Hugging Face, Matplotlib, or similar) under the 'What you have done' requirements section. PyTorch and scikit-learn are listed as alternatives to each other ('or similar' framing within the same list); all others are treated as individually required.
Polars appears in the same library list as pandas but is a less universally expected tool; it is marked preferred given the 'or similar' qualifier on the whole list.
AI coding assistants (Claude Code, Cursor, or similar) appear in the 'What you have done' section but read more as a workflow expectation than a hard technical gate; marked preferred accordingly.
Causal inference, uncertainty quantification, and HIPAA/PHI experience appear under 'What gives you an edge' (the nice-to-have section) and are marked preferred.
No compensation figures are disclosed in the posting.
The posting describes a hybrid Bay Area role (Mon–Thu in office), but the caller has declared this fully remote with a national candidate pool; remote=true and no metro are set per that instruction.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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