Staff ML Engineer: Build Core MLOps & Models (Hybrid)

Jack & Jill; San Francisco (CA); Hybrid; USD 220,000 - 270,000; Full time

Benefits offered by this job

100% employer-paid healthcare premiums

Hybrid work flexibility

Job summary

Sprinter Health is hiring its first dedicated Staff Machine Learning Engineer in San Francisco to build production ML systems, from training to deployment and monitoring, shaping the company-wide MLOps blueprint.

You will collaborate with product, data and applied science teams to turn research prototypes into reliable APIs and batch jobs that power patient-centered care, with a strong emphasis on observability and governance.

Qualifications

• 8+ years of experience in production software and ML systems.
• Deep expertise in cloud infrastructure, containerization, and MLOps paradigms.
• Thrives in ambiguous startup environments with architectural longevity and speed.

Responsibilities

• Build and lead the ML engineering function, designing the foundational infrastructure for model training, real-time serving, and feature pipelines.
• Implement robust monitoring and observability systems to detect drift, data quality issues, and performance regressions.
• Package models into reliable APIs and batch jobs powering Sprinter Health’s core marketplace.

Tools

Docker

Kubernetes

Terraform

Job description

Sprinter Health is hiring its first dedicated Staff Machine Learning Engineer in San Francisco to build production ML systems, from training to deployment and monitoring, shaping the company-wide MLOps blueprint.

You will collaborate with product, data and applied science teams to turn research prototypes into reliable APIs and batch jobs that power patient-centered care, with a strong emphasis on observability and governance.