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Sprinter Health

AI Research Scientist

San Francisco, CA; Menlo Park, CAHybrid · United States
FullTime · Sprinter Health
POSTED 17 JULVERIFIED 1D AGO
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Role
114 days opentrue age
Posted 17 Jul
Payats field
$160k–220kposted
▼ −24% vs market median $250k
$160k$300k
Market p25–p75
$200k–$300k
SF Bay Area · n=461 · 365d to 6 Nov
CompanySprinter Health →
52open roles
Opened · 30d
+0
Closed · 30d
−0
30d window
Market
3,285open · ML / AI
Opened · 7d
+1846% of open
All ml / ai
6,677open
All tracked boards · live 9 Nov · n=3,285

About Sprinter Health

At Sprinter Health, our mission is reimagining how people access care by bringing it directly to their homes. Nearly 30% of patients in the U.S. skip preventive or chronic care simply because they can’t get to a doctor’s office. For many, the ER becomes their first touchpoint with the healthcare system—driving over $300B in avoidable costs every year.

By using the same technologies that power leading marketplace and last-mile platforms, we deliver care where people are, especially those who need it most. So far, we’ve supported more than 2 million patients across 22 states, completed 130,000+ in-home visits, and maintained a 92 NPS. Our team of clinicians, technologists, and operators have raised over $125M to date investors like a16z, General Catalyst, GV, and Accel and enjoy multi-year runway.

About the Role

We’re looking for an AI Research Scientist to advance the methodological frontier of AI in healthcare. This role is ideal for someone who has demonstrated strong research taste, deep technical foundations, and the ability to turn open-ended problems into rigorous scientific contributions.

You will develop and own a research agenda aligned with Sprinter’s company strategy. Your work may include novel architectures, new training or evaluation techniques, long-horizon research bets, peer-reviewed validation studies, patents, and methods that ultimately graduate into production systems.

The ideal candidate is deeply technical, scientifically rigorous, and excited to collaborate closely with clinicians, product leaders, and applied AI teams. You understand that healthcare validation standards are higher than benchmark culture alone, and you are energized by the opportunity to produce research that is both scientifically meaningful and practically impactful.

Hybrid & Office Experience

We operate on a hybrid schedule, working from the office Monday through Thursday, with Fridays designated as work-from-anywhere days.

We care deeply about work-life balance and are happy to provide flexibility when life happens. We ask that employees be in the office Monday through Thursday to collaborate with their teams while maintaining flexibility where it matters most.

Lunch is provided every day, and the entire team takes an hour to eat together. It's one of the ways we stay connected outside of meetings. You'll usually find us playing a board game before getting back to work.

What you will do

Research Agenda & Scientific Contribution

Develop and own a research agenda aligned with Sprinter’s long-term AI and company strategy.

Identify open problems, position them against the literature, and design experiments that isolate meaningful contributions.

Develop novel methods, architectures, training approaches, evaluation techniques, or validation frameworks.

Produce publications, patents, peer-reviewed validation studies, and other evidence artifacts.

Translate promising research into methods and tools that applied teams can use in production.

Technical Leadership

Raise the scientific bar across applied AI and engineering teams.

Review methodologies, evaluation approaches, and experimental designs.

Advise teams on hard technical decisions, especially around model performance, reliability, evaluation, uncertainty, and validation.

Help determine whether a result is meaningful, reproducible, or an artifact.

Mentor applied researchers and engineers on rigorous ML research practices.

External Presence & Collaboration

Maintain an external research presence through publications, talks, academic collaborations, and participation in relevant research communities.

Collaborate with clinical partners on validation studies, including work that may involve IRB review, data governance, external validation, or prospective evaluation.

Partner cross-functionally with Product, Clinical, Engineering, and Leadership teams to ensure research priorities map to meaningful company and patient impact.

What you have done

Demonstrated ability to produce novel research, including identifying open problems, designing rigorous experiments, and writing work to a peer-review standard.

Source · Sprinter HealthFirst seen 7 NovOriginal ↗