Software Engineer - Core Systems
Epsilon Health · San Francisco, CA
About this role
## About Epsilon Health Epsilon Health is transforming medical imaging and diagnostics by bringing frontier AI into clinical practice. We’ve served **300,000+ patients** and now support **3,000+ daily**, working with major medical institutions across the U.S. Our research team brings experience from **DeepMind** and **Meta**, powered by a comprehensive proprietary medical imaging dataset continuously enriched with real-world clinical data. Recently out of stealth, we’re backed by **Jack Altman**, **Uncork Capital**, **Renegade Partners**, and **AlleyCorp**. --- ## Role Overview — Software Engineer (Core Systems) We’re looking for Software Engineers to build and operate the **core infrastructure** powering Epsilon Health, including: - **Ingestion pipeline** - **Data warehouse / pipeline** - **Distributed inference system** You’ll work across the backend stack—designing services, evolving schemas, improving observability, and keeping production healthy. This is not a “single microservice” role. We expect you to understand how the system fits together, make thoughtful architectural decisions, and leave the system simpler than you found it. We also don’t have a separate SRE organization—**reliability, operations, debugging, and capacity planning** are part of engineering here. You’ll collaborate closely with the ML team and support ML infrastructure when priorities demand. --- ## Key Responsibilities - Design, build, and operate infrastructure delivering **reliable end-to-end experiences** from data ingestion through model output. - Build robust **data pipelines and warehouses** to collect, process, and store large-scale multimodal medical imaging data from production and offline sources. - Develop **CI/CD and deployment automation** to enable a lean team to ship quickly and safely. - Ensure systems handling **PHI** are **HIPAA-compliant by design**, including encryption, access controls, audit logging, and secure data handling. - Build **model inference pipelines** for live and offline traffic; support ML infrastructure alongside the ML team. - Lead technical design, drive quality via design reviews and testing, and help establish engineering best practices on a lean team. --- ## Qualifications - **6+ years** building data infrastructure, storage systems, or related distributed systems. - **2+ years** leading large-scale, complex projects or teams as an engineer or tech lead. - Proficiency in a backend language: **Go, Python, Java, or similar**. - Experience designing, building, and operating **large-scale distributed systems/infrastructure** in production (we use **AWS**). - Strong problem-solving and ability to troubleshoot complex distributed systems. - Ability to navigate tradeoffs across **performance, cost, security, and maintainability**. - Track record leading complex, multi-quarter initiatives across multiple teams/systems. --- ## Preferred Qualifications - Experience in a startup or startup-like environment (small, fast-moving team with high autonomy). - Frontend web tech proficiency (e.g., **TypeScript, React**) and strong web architecture understanding. - Experience operating **HIPAA-compliant systems** / handling PHI and healthcare security requirements. - Experience with large-scale **ETL**, data lake, or data warehouse systems. - Experience contributing to **ML infrastructure** or **model inference pipelines**. --- ## Compensation The anticipated annual base salary for this position is **up to $250,000**. This
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