Backed by Battery and GV.
About the role
We're seeking a hands-on, technically deep Sr/Director of Engineering to lead our ML Engineering team! You will manage and grow a team of engineers who build and own the core AI/ML platform for the company, and running it at massive scale. You will also serve as a key thought partner to our Chief AI Officer, bridging the gap between data science proof-of-concepts and scalable, production-grade services.
What they're looking for
- BS or MS in Computer Science (or equivalent experience)
- 5+ years managing teams of ~8+ engineers with hands-on technical leadership
- 8+ years direct hands on technical contributor in backend services experience
- 3+ years specifically building AI/ML production-grade services at scale for multiple use cases. Direct co-working with data science and engineering
- Strong in Java, Scala, Rust, or similar backend languages, plus Python
- Understanding of what it takes to productize ML/AI platforms — workflows, serving, observability, reliability, and scale
More about this role
Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
We're seeking a hands-on, technically deep Sr/Director of Engineering to lead our ML Engineering team! You will manage and grow a team of engineers who build and own the core AI/ML platform for the company, and running it at massive scale. You will also serve as a key thought partner to our Chief AI Officer, bridging the gap between data science proof-of-concepts and scalable, production-grade services.
The ideal candidate blends AI/ML engineering depth with applied data science fluency. You understand what it takes to productize AI/ML capabilities — serving, observability,...
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