We're tackling one of healthcare's most critical challenges in medical imaging and diagnostics. Our company operates at the intersection of cutting-edge AI and clinical practice, building technology that directly impacts patient outcomes. We've assembled one of the industry's most comprehensive and diverse medical imaging datasets and have a proven product-market fit with a substantial customer pipeline already in place.
Role OverviewThis is a unique opportunity for a strong generalist engineer who thrives in ambiguity, loves solving complex problems, and wants to have outsized impact. You'll work alongside our ML team to build the foundation that will scale our technology to millions of patients.
As a critical member of our lean engineering team, you'll wear multiple hats - from designing APIs and shipping production features, to building robust ML infrastructure and optimizing system performance.
Key ResponsibilitiesDesign, develop, test, deploy, and operate fully integrated solutions that provide seamless end-to-end experiences
Lead technical design decisions for major product features
Design, build, and maintain infrastructure for modern integration methods between our applications and our customers’ applications
Collaborate extremely effectively with internal users (technical and non-technical), other engineers, stakeholders, and vendors on projects within the team and across the company to understand requirements and translate them into technical solutions.
Communicate technical ideas and work closely with other senior members of the team
Mentor team members and establish engineering best practices
Take ownership of large projects from conception to deployment
Drive architecture and code quality through rigorous testing, thoughtful design reviews, and scalable engineering practices that ensure performance, reliability, and maintainability across the stack
Design and develop a centralized ETL, data lake, and data warehouse solution for hundred of terabytes of data
Build and optimize ML model inference pipelines for both live traffic and offline data.
Develop a comprehensive framework shared across ML research and product traffic to validate model performance on diverse clinical scenarios
Design and build an experimentation framework that will allow ML scientists to quickly A/B test multiple ML models
Design a reliable, robust cloud-based networking infrastructure that allows seamless onboarding and integration multiple (potentially infinite) external sites
5+ years of experience as a software engineer, demonstrably delivering on time, at quality
Full stack experience with emphasis on the BE and infrastructure:
Experience in a backend language such as Go, Python, Java, or similar
Experience with cloud platforms and distributed architectures, specifically with AWS
Have hands-on experience with schema design and data modeling
Strong experience designing and building backend infrastructure (API, ML infrastructure, data pipeline) that is reliable, scalable and easy to maintain
Strong problem-solving skills and the ability to troubleshoot complex systems.
Have experience shipping things quickly with competing priorities or deadlines
Are a team player, willing to do a variety of tasks that move the team forward
Excellent communication skills and ability to work cross-functionally
Top Skills
What We Do
Epsilon Health exists to solve the looming global radiology crisis before it reshapes patient care. Radiology underpins nearly every medical specialty, yet it is one of the most strained parts of the healthcare system. We’re rethinking how imaging and interpretation work to make radiology faster, more reliable, and future-proof.
