- Build systems that help teams train, evaluate, deploy and serve machine learning models and AI features.
- Develop backend services, Python libraries, and model lifecycle tooling.
- Create and maintain evaluation workflows and low-latency serving systems.
- Collaborate with internal ML engineers, scientists, and product teams.
- Ensure production ML systems remain reliable, observable, and safe.