Software Engineer, Statistical Evaluation and Sampling

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About this role

Software Engineer, Statistical Evaluation and Sampling Mountain View, CA, USA; San Francisco, CA, USA 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. Waymo's Release Evaluation org ensures that each version of the Waymo Driver is safe before it hits the road. We build automated pipelines to solve the long tail of rare and exceptional scenarios in autonomous driving, looking for needles in a haystack under both time and resource constraints. Within Release Evaluation, the Sampling and Efficiency team applies importance sampling techniques and machine learning to maximize the statistical efficiency of these discovery pipelines. You will: - Develop importance sampling techniques that enable our evaluation pipelines to deliver better signals with fewer resources. - Find signals in our logs and simulations that might help us to more efficiently discover rare and important events. - Build systems that systematically optimize multiple objectives under resource constraints. - Collaborate with

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