Software Engineer, ML Efficiency

Waymo is an autonomous driving technology company with the mission to be the world's 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’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15 U.S. states.

The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

This role follows a hybrid work schedule and you will report to a Principal Research Scientist.

You Will

• Enable the team to develop large scale end-to-end driving models with high hardware efficiency, reliable training and inference, and good developer experience
• Participate in model design from a hardware-efficiency's perspective
• Partner with other Waymo and Google teams to collaborate on infra work
  
  

You Have

• Bachelor degree in Computer Science, similar technical field of study, or equivalent practical experience
• Proficiency in writing and debugging Python/numpy-style code
• Proficiency and in-depth knowledge of the inner workings of an ML framework (e.g. Pytorch, JAX, Tensorflow)
• Proficiency in system performance: parallelism, buffering/prefetching and pipelining, and asynchronicity
  
  

We Prefer

• Experience with large scale system reliability and failure-resilience/recovery
• Expertise in ML accelerator programming, including but not limited to CUDA, Triton, or ML compilers
• Knowledge of hardware micro-architectures and instruction sets
• Proficiency in C
  
  

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range

$204,000—$259,000 USD