ML Infrastructure Engineer: Scalable Training and Deployment

Epsilon Health in San Francisco is seeking an ML infrastructure engineer to design core systems for scalable training of large models in medical imaging. You will enable researchers to run experiments efficiently, focusing on science rather than bottlenecks.

In this role you own distributed training, data loading, inference and deployment pipelines, and the RL training stack; collaborate with research and backend teams to ship production-grade solutions.

This role, ML Infrastructure Engineer:
Scalable Training and Deployment at Epsilon, could be your next opportunity.

This is a great role to take on the ML Infrastructure Engineer:
Scalable Training and Deployment role at Epsilon.

As a ML Infrastructure Engineer:
Scalable Training and Deployment, you will play an important part at Epsilon in San Francisco, CA, United States.

We invite applications for the ML Infrastructure Engineer:
Scalable Training and Deployment position located in San Francisco, CA, United States.