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 Simulator team builds state of the art simulations of realistic environments for the testing and training of the Waymo driver. We use machine learning to model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather. To guide the development of simulator realism components, we create metrics to measure realism, which are used to assess the quality of the simulator, identify sim2real gaps, and used as loss functions to train a more realistic simulator - which in turn is used to assess the quality of the Waymo Driver.
In this hybrid role you will report to an Engineering Director.
You will:
- Develop novel methods to measure sim realism in the context of several simulator tech and applications
- Develop efficient platform to allow measuring sim realism at scale
- Design systems that can automatically discover useful realism metrics to guide simulator development
- Collaborate with a world-class engineering and research team that use large models to improve sim realism
- Be a part of a collaborative engineering team that build a realistic simulator which powers the evaluation of the Waymo Driver
You have:
- Coding and design skills
- 5+ years of experience navigating a complex product space and setting technical roadmaps
- 5+ years of experience building scalable infrastructure, or in evaluating complex systems
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.
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