Staff ML Infra Engineer: Scalable Training & Pipelines

Watney Robotics Inc; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Watney Robotics is seeking an ML Infrastructure engineer to turn data from a live robot fleet into better models. You will own training and inference infrastructure, build data pipelines, and ensure rapid, reproducible experiments while contributing to core training code.

We value diverse backgrounds and encourage applicants who are passionate about robotics, even if not all requirements are met. This role is ideal for advancing scalable ML in real-world robotics contexts.

Qualifications

• Built ML infrastructure that supported production training runs.
• Experience scaling distributed training systems.
• Strong Python experience with ML frameworks (PyTorch or TensorFlow).
• Ability identify and troubleshoot GPU bottlenecks in large-scale training.

Responsibilities

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

Skills

ML infrastructure

Python

PyTorch

TensorFlow

Distributed training

GPU performance

Job description

Watney Robotics is seeking an ML Infrastructure engineer to turn data from a live robot fleet into better models. You will own training and inference infrastructure, build data pipelines, and ensure rapid, reproducible experiments while contributing to core training code.

We value diverse backgrounds and encourage applicants who are passionate about robotics, even if not all requirements are met. This role is ideal for advancing scalable ML in real-world robotics contexts.