$215K to $275K a year as published by the employer
Applications are completed on the employer's own site.
Design, build, and operate backend infrastructure for data ingestion, warehousing, and distributed model inference on AWS while ensuring HIPAA compliance.
About the RoleJoin a small engineering team at an early-stage healthtech company, building the backend infrastructure for a radiology platform. You will own key systems that support medical imaging data pipelines and AI model inference, helping improve the reliability and scale of tools used in radiology. What You'll DoDesign, build, and operate backend infrastructure for data ingestion, warehousing, and distributed model inference on AWS.
Own reliability, observability, debugging, and capacity planning across the systems you support.
Build CI/CD and deployment automation that enables the team to ship safely and efficiently.
Design systems that handle protected health information with encryption, access controls, audit logging, and HIPAA compliance in mind.
Partner with the ML team on infrastructure and model inference pipelines as priorities require.
What We're Looking ForAt least 5 years of experience in backend engineering, data infrastructure, or distributed systems, with hands-on production experience at scale.
Proficiency in Go, Python, or Java, and experience building and operating distributed systems on AWS or a comparable cloud.
Depth in data infrastructure, including large-scale pipelines, ETL, warehouses or data lakes, schema evolution, and deployment automation.
Experience leading multi-quarter technical initiatives across systems or teams, and working on a small, fast-moving team.
Strong skills in troubleshooting distributed systems and balancing performance, cost, security, and maintainability.
Exposure to ML infrastructure or model inference pipelines, HIPAA-compliant system design, and TypeScript or React is useful.
A STEM degree or strong computer science fundamentals.
Compensation & BenefitsBase salary: $215,000 to $275,000 annually. Visa sponsorship is available. LocationOn-site in San Francisco, California, United States.
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