Staff Software Engineer - ML Infrastructure

The role

ML Infrastructure engineers turn data collected from a live fleet of robots into better models. You will own training and inference infrastructure and build data pipelines for training runs.

What you will do

• Own training and inference infrastructure.
• Build the data pipelines that these training runs depend on.
• Make experiments fast to launch and reproduce.
• Contribute to our core training code.

Required qualifications

• Have built ML infrastructure that carried real production training runs.
• Have scaled distributed training systems.
• Strong experience with Python, PyTorch or TensorFlow.
• Have experience identifying and troubleshooting GPU performance bottlenecks in large-scale training environments

About the company

Watney builds and deploys autonomous robotic systems that increase the speed and capacity of buildout, starting with data centers.