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:

  • Analyze the performance characteristics of code generated by our production grade compiler and develop and implement engineering roadmaps for its improvement
  • Architect, design, and implement compiler support for novel features of our unique neural network inference platform
  • Guide model developers and hardware architects towards improving the efficiency and achieved performance of inference hardware via software/hardware codesign

At a minimum we'd like you to have:

  • Relevant education/work experience
  • BS degree in Computer Science/Electrical Engineering or equivalent practical experience and 7+ years of industry experience OR
  • MS degree in Computer Science/Electrical Engineering and 5+ years of industry experience OR
  • PhD degree in Computer Science/Electrical Engineering and 3+ years of industry experience
  • 3+ years of industry and/or academic experience working on compilers for neural networks or linear algebra computation targeting parallel architectures
  • 1+ years of experience in techniques used to generate code optimized for performance on a parallel architecture
  • Strong C++ programming skills

It's preferred if you have:

  • Python programming experience
  • 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

US-Remote includes employees working from their primary residence in certain locations only, such as Arizona, California, Colorado, Connecticut, DC, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, Nebraska, New Jersey, New York, North Carolina, Ohio, Oregon, Pennsylvania, South Carolina, Texas, Utah, Virginia, Washington, and Wisconsin. This list may not be complete or accurate, and candidates should speak with their recruiter about their specific location for remote work.

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$226,000$286,000 USD

Salary

$226,000 - $286,000

Yearly based

Location

Mountain View (US-MTV-EMF680), New York City (US-NYC-9TH)

Job Overview
Job Posted:
5 months ago
Job Expires:
Job Type
Full Time

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