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Staff Machine Learning Engineer, Inference
2 months ago
About Waymo
Waymo is a leading autonomous driving technology company with a mission to be the most trusted driver. Since its inception in 2009 as the Google Self-Driving Car Project, Waymo has focused on building the Waymo Driver - The World's Most Experienced Driver - to improve access to mobility while saving thousands of lives lost to traffic crashes.
The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.
About the Role
We are seeking a highly skilled Machine Learning Engineer to join our team and focus on developing large-scale and efficient inference solutions for Waymo. This is crucial to the development of Waymo Foundation Models for driving, including evaluation, auto-labeling, and distillation.
Responsibilities
- Develop and implement large-scale and efficient inference solutions for Waymo
- Collaborate with machine learning experts across the company and Alphabet to ensure consistency and repeatability
- Work on feature and experiment management, model development, debugging, and evaluation, deployment, and monitoring
- Contribute to the development of Waymo Foundation Models for driving
Requirements
- B.S. in Computer Science, Math, or equivalent real-world experience
- 2+ years of experience as a technical lead
- 5+ years working with high-scale distributed or ML inference systems for real-time and batch processing
- Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow
Preferred Qualifications
- MS in Computer Science, Math, or equivalent real-world experience
- Experience with multi-threaded and stream-based programming models
- Prior experience on ML compiler optimization such as TVM or XLA
- Previous experience deploying machine learning models for computer vision, natural language processing, or recommendation systems
