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Machine Learning Engineer

Remote Posted Jul 28, 2026 0 views

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Job description

Sprinter HealthJobs
Machine Learning Engineer

Machine Learning Engineer

Posted Yesterday
San Francisco CA USA
Hybrid
140K-200K Annually
Mid level
Artificial Intelligence • Healthtech • Logistics • Social Impact • Software • Telehealth
Sprinter Health leverages last mile delivery technology and AI to close healthcare accessibility gaps across the US.
The Role
Build and maintain production ML systems: training and inference pipelines model packaging and serving feature pipelines monitoring for drift and degradation automated retraining and reproducibility/versioning across data and models.
Summary Generated by Built In

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 130000+ 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 ML Engineer to build the production systems that train deploy monitor retrain and serve our machine-learning models reliably. You sit between software engineering data engineering and modeling and you make ML work in the real world and stay working.

You will build training and inference pipelines serve predictions through APIs and batch jobs and stand up the monitoring that catches drift and silent degradation before they reach a patient or a partner. You will turn the models that scientists prototype into systems the company can depend on.

The ideal candidate thinks in systems rather than notebooks knows what a model needs to become production-ready and builds clean interfaces between data models and product.

 

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:

Production ML Systems
  • Build and harden training pipelines.

  • Package models for deployment.

  • Serve predictions through APIs or batch jobs with reliability in mind.

  • Maintain feature pipelines and keep features fresh and correct.

Reliability & Observability
  • Monitor drift data quality latency cost and performance.

  • Automate retraining and validation and design safe rollback.

  • Prevent training-serving skew and silent model degradation.

Collaboration & Craft
  • Productionize models handed off from other teams.

  • Build clean interfaces between data model and product systems.

  • Implement reproducibility versioning and model-governance artifacts..

 

What you have done:

  • Strong Python and software-engineering fundamentals.

  • Experience with ML frameworks data pipelines and model serving.

  • Experience taking models from prototype to reliable production.

  • Cloud infrastructure containers CI/CD and orchestration.

  • Monitoring and observability plus reproducibility and versioning across data features and models.

  • Comfort with security and privacy controls for sensitive data.

 

What gives you an edge:

  • Background in backend engineering data engineering MLOps or platform engineering.

  • Experience with feature stores or feature pipelines at scale.

  • Familiarity with healthcare data and PHI-aware systems

 

Interview Process:

  • We aim to complete the interview process between 2–3 weeks. It will usually consist of:

    • Recruiter Screen (30 minutes)

    • Hiring Manager Introduction (30 minutes)

    • Hands-on-Keys Technical Assessment (1 hour)

    • Onsite Interview: Systems Design / Technical Case Study + Research Presentation + Behavioral Interview + Lunch with the Team (4 hours)

    • References

 

What we offer:

  • Meaningful pre-IPO equity

  • Medical dental and vision plans 100% paid for you and your dependents

  • Flexible PTO + 10 paid holidays per year

  • 401(k) with match

  • 16-week parental leave policy for birthing parent 8 weeks for all other parents

  • HSA + FSA contributions

  • Life insurance plus short and long-term disability coverage

  • Free daily lunch in-office

  • Annual learning stipend

Skills Required

  • Strong Python and software engineering fundamentals
  • Experience with ML frameworks data pipelines and model serving
  • Experience taking models from prototype to reliable production
  • Experience with cloud infrastructure containers CI/CD and orchestration
  • Experience with monitoring and observability reproducibility and versioning for data features and models
  • Comfort with security and privacy controls for sensitive data (PHI-aware practices)
  • Background in backend engineering data engineering MLOps or platform engineering
  • Experience with feature stores or feature pipelines at scale
  • Familiarity with healthcare data and PHI-aware systems

What the Team is Saying

Josh
Dara
Wes
Sharmane
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The Company
Menlo Park CA
500 Employees
Year Founded: 2021

What We Do

At Sprinter Health we're focused on dramatically expanding access to healthcare by reimagining the patient experience—delivered at home and powered by technology for scale. We’re a boots-on-the-ground clinician network for the tele-health age bringing routine blood draws labs and vitals checks into people's busy lives. We have completed over 140000 appointments in 2025 across the US!

Why Work With Us

Sprinter Health is reinventing access to care founded by the co-founder of Oculus in 2020. With tech AI and an incredible clinical team we bring preventive care into patients’ homes—reaching the vulnerable communities the healthcare system often misses. Join us in a supportive flexible family-friendly culture.

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Sprinter Health Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 3 days a week
Menlo Park CA
San Francisco Bay Area
Learn more

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