Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver - The World's Most Experienced Driver - to improve access to mobility while saving thousands of lives now 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.
Find out exactly what skills, experience, and qualifications you will need to succeed in this role before applying below.
Waymo's Compute Team is tasked with a critical and exciting mission : We deliver the compute platform responsible for running the fully autonomous vehicle's software stack.
To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency;
and we collaborate with many other teammates to ensure we design and optimize hardware and software for maximum performance.
We are a diverse team looking for curious and talented teammates to work on one of the world's highest performance automotive compute platforms.
In this hybrid role, you will report to a Software Engineering Manager.
You will :
- Analyze the performance characteristics of code generated by our production grade compiler, and design and implement optimizations to improve that performance.
- Design and implement compiler support for novel features of our high-performance architecture.
- Work with hardware architects to understand and influence the development of our unique neural network inference platform through hardware / software codesign.
- Work with model developers to tune their neural networks for better inference efficiency and accuracy.
You have :
- BS degree in Computer Science / Electrical Engineering or equivalent practical experience and 5+ years of industry experience OR
- MS degree in Computer Science / Electrical Engineering and 3+ years of industry experience.
- PhD degree in Computer Science / Electrical Engineering and 1+ years of industry experience.
- 3+ years experience working on compilers for parallel architectures.
- 1+ years experience working with ML inference or linear algebra computation.
- C++ programming skills.
We prefer :
- Python programming experience.
- Experience with compilers for neural networks.
- Knowledge of computer architectures used for neural network inference, and neural network performance characteristics.
- Knowledge of the principles behind popular machine learning and neural network algorithms and applications.
LI-Hybrid
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