Machine Learning Engineer (Staff)

Sprinter Health
San Francisco, Menlo Park
Workplace: HybridFull timeUSD 220,000 - 270,000 annuallyFunction: Data Science & Machine LearningExperience: 8+ yearsSkills: ["Systems thinking","Stakeholder collaboration","Technical leadership","Mentoring","Communication"]

Build and lead the company’s first dedicated machine learning engineering function, defining the production blueprint for training, deployment, monitoring, retraining, and governance. Design reliable training and inference pipelines, package models for APIs and batch jobs, and create feature and data interfaces that are safe and maintainable. Implement end-to-end observability to detect drift, data issues, latency, and cost regressions, while standardizing deployment workflows and partner handoffs across engineering and data teams.

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FursaFursa
Sprinter Health
Sprinter Health
1 month ago

Machine Learning Engineer (Staff)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Build and lead the company’s first dedicated machine learning engineering function, defining the production blueprint for training, deployment, monitoring, retraining, and governance. Design reliable training and inference pipelines, package models for APIs and batch jobs, and create feature and data interfaces that are safe and maintainable. Implement end-to-end observability to detect drift, data issues, latency, and cost regressions, while standardizing deployment workflows and partner handoffs across engineering and data teams.
Location: San Francisco, Menlo Park
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build and lead the ML engineering function as Sprinter’s first dedicated ML engineering hire.
  • •Define the ML platform and deployment paradigm across training, serving, features, monitoring, retraining, and governance.
  • •Design and implement production training and inference pipelines, including packaging models for APIs and batch jobs.
  • •Create and maintain feature pipelines and interfaces between data, models, and product systems.
  • •Implement observability and automation for validation, rollback, monitoring, and retraining while preventing drift, skew, and silent degradation.

Pay and Benefits

Salary: USD 220,000 - 270,000 annually
Equity and Bonus:Equity
Perks:EquityHealth InsuranceDentalVision401kParental LeaveHsaFsaLife InsuranceDisability CoverageLearning BudgetRelocationMeal AllowancePaid Holidays

Key Requirements

  • •8+ years building production software, data systems, ML systems, or related technical infrastructure.
  • •Experience building and owning ML systems in production across training, serving, features, monitoring, and deployment.
  • •Track record taking prototypes or research-stage models into reliable, production-grade systems.
  • •Hands-on background scaling ML infrastructure and MLOps platforms, model serving systems, and feature pipelines.
  • •Experience with cloud infrastructure and production workflows, including containers, CI/CD, orchestration, data pipelines, and observability.
Experience:8+ yearsMLOpsHealthcareReal-time inferenceLLM infrastructure
Skills:Systems thinkingStakeholder collaborationTechnical leadershipMentoringCommunication
Tech Stack:Machine learningMLOpsCI/CDContainersOrchestrationData pipelinesModel monitoringObservabilityFeature pipelines

Company Brief

Sprinter Health
Operates mobile and home-based primary care services focused on delivering in-home medical visits, chronic care management, and coordinated care for patients who face barriers accessing clinic-based care.
Industry: Healthcare Providers
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