Staff Software Engineer, Quantitative Evaluation
Waymo - Mountain View, California, United States; San Francisco, California, United States; New York City, New York, United States.
Posted May 23, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
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About this role
Staff Software Engineer, Quantitative Evaluation Mountain View, California, United States; San Francisco, California, United States; New York City, New York, United States. 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 Driverâ„¢-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 Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you! In this hybrid role, you will report to an Engineering Manager. You will: - Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and
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