Frontier AI for medical imaging, built and deployed inside a working radiology practice.
About the role
We’re looking for an ML infrastructure engineer to design and build the core systems that enable scalable, efficient training of large models for deployment and research. Your goal is to make experimentation and training at Epsilon Health fast and reliable to ensure our research teams can focus on science rather than system bottlenecks. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 6+ years of experience designing, building, and operating large-scale distributed systems or infrastructure in production
- Have 2+ years of experience building ML infrastructure or systems in production
- Strong Python skills and expertise in PyTorch or JAX
- Experience and familiarity with the compute, tooling, and workflow needs of large-scale machine learning research
- Experience building infrastructure or platforms specifically for research or machine learning workflows
- Deep experience building and operating Kubernetes and cloud infrastructure at scale
More about this role
Epsilon Health is transforming medical imaging and diagnostics by bringing frontier AI into clinical practice. We're tackling some of healthcare's most critical challenges, building technology that directly improves patient outcomes.
This year, we've served over 300,000 patients and now serve 3,000+ daily, working with some of the largest medical institutions in the U.S. By year-end, we're on track to interpret 1% of all daily U.S. X-rays.
Our research team brings experience from DeepMind and Meta, powered by one of the industry's most comprehensive proprietary medical imaging datasets, continuously enriched by real-world clinical data. Together, we're building a future where frontier AI helps save millions of lives today, not tomorrow.
Recently out of stealth, we're proudly backed by Jack Altman, Uncork Capital, Renegade Partners, and AlleyCorp, one of NYC's most active healthcare venture firms.
We’re looking for an ML infrastructure engineer to design and build the core systems that enable scalable, efficient training of large models for deployment and research. Your goal is to make experimentation and training at Epsilon Health fast and reliable to ensure our research teams can...
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