Join a small engineering team building the backend infrastructure for a radiology-focused healthcare platform and its AI copilot. You will own critical systems across data ingestion, warehousing, and distributed model inference, helping make the platform reliable and ready to scale.
Design, build, and operate backend infrastructure for data ingestion, warehousing, and distributed model inference on AWS.
Own reliability, observability, debugging, and capacity planning across the stack.
Build CI/CD and deployment automation that supports fast, safe releases.
Design systems that handle protected health information with encryption, access controls, and audit logging.
Partner with the ML team on infrastructure and model inference pipelines as priorities evolve.
At least 5 years of experience in backend engineering, data infrastructure, or distributed systems, with substantial experience building and operating production systems.
Strong proficiency in Go, Python, or Java, and hands-on experience with AWS or a comparable cloud platform.
Depth in data infrastructure, including large-scale pipelines, ETL, warehouses or data lakes, and schema evolution.
Experience leading multi-quarter technical initiatives across systems or teams, and making thoughtful tradeoffs among performance, cost, security, and maintainability.
Familiarity with CI/CD, deployment automation, and troubleshooting complex distributed systems.
Startup or startup-like experience is valuable. Experience with ML infrastructure, model inference, HIPAA or protected health information, and TypeScript or React is a plus.
A STEM degree or strong computer science fundamentals.
Annual salary range: $215,000 to $275,000 USD. Visa sponsorship is available.
On-site in San Francisco, California, United States.
Job details are sourced from the employer's original posting.
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