Senior Core Systems Engineer - Data Infrastructure

Epsilon Health; San Francisco (CA); On-site; USD 150,000 - 250,000; Full time

Job summary

Epsilon Health is building the core infrastructure for medical imaging AI in the United States. You will design, build, and operate the data ingestion pipeline, data warehouse, and a distributed inference system that powers clinical practice.

You’ll work across the backend stack, shaping schemas, improving observability, and keeping production healthy. Collaboration with the ML team is essential as you own ambiguous, high-impact problems end to end.

Qualifications

• 6+ years of experience building data infrastructure or distributed systems.
• 2+ years leading large-scale 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 in production (AWS).
• Strong problem-solving skills and ability to troubleshoot complex systems.
• Ability to navigate tradeoffs between performance, cost, security, and maintainability.
• Track record of leading multi-quarter technical initiatives across teams.

Responsibilities

• Design, build, and operate infrastructure delivering end-to-end experiences from data ingestion through model output.
• Design and implement robust data pipelines and warehouses for large-scale multimodal imaging data.
• Build CI/CD and deployment automation for a lean team.
• Ensure PHI-handling systems are HIPAA-compliant by design with encryption and auditable access controls.
• Build model inference pipelines for live and offline traffic and support ML infrastructure.
• Lead technical design, drive quality via design reviews, and set engineering best practices in a lean team.

Skills

Go

Python

Java

AWS

Distributed systems

HIPAA compliance

Tools

CI/CD

Data pipelines

Data warehouse

ML infrastructure

Job description

Epsilon Health is building the core infrastructure for medical imaging AI in the United States. You will design, build, and operate the data ingestion pipeline, data warehouse, and a distributed inference system that powers clinical practice.

You’ll work across the backend stack, shaping schemas, improving observability, and keeping production healthy. Collaboration with the ML team is essential as you own ambiguous, high-impact problems end to end.