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.

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 closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world’s highest performance automotive compute platforms.

In this role, you'll:

• Collect application/ML model performance traces and analyze for performance optimization opportunities
• Land the optimizations to the application/ML model code base by
  • Evaluating the correctness of the change (including retraining the ML model to evaluate accuracy)
  • Ensure the change is net-positive for the current onboard performance
  • Work with the application teams to apply the optimization
  • Add proper testing to ensure optimized performance is tracked and not regressed in the future
• Land the optimizations to the infrastructure by
  • Prototype the performance optimizations and evaluate its effectiveness on applications/ML models
  • Generalize the optimization at the infra level (compiler, firmware, runtime, framework, etc.) and project the potential impact to all applications (ML models) across board
  • Motivate the Infrastructure teams to land the optimization to the specific level of the stack, set the performance expectation through solid methodology (e.g. roofline) and ensure the Infrastructure team is aligned about the expectation
  • Once the optimization is landed by the Infrastructure teams, close the loop by evaluating the overall performance impact and ensure it’s landed in the expected way

At a minimum we’d like you to have:

• Bachelors in Computer Science or Electrical Engineering
• Proficient in C++ and Python
• Experience with application performance optimization
• Proficiency in collaboration with teams in US

It's preferred if you have:

• ML performance and compiler
• Computer architecture and performance analysis methodologies
• Robotic application development/optimizations