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. The Perception Scene Semantics team is responsible for developing ML models for scene understanding around construction, emergency scenes, mapless driving and world changes. The team works on the end to end ML pipeline from data mining, labeling, training onboard / offboard models, and deployment. We need someone with strong ML experience to drive the architecture upgrades and product feature development. In this hybrid role, you will report to a TLM within Perception Semantics. You Will Design and implement new evaluation systems and strategies to measure the safety and performance of large-scale Waymo Perception machine learning models and support onboard engineers in both regression prevention and quality hillclimbing. Make evaluation-driven recommendations for modeling and data changes and actively influence deployment of onboard models. Create evaluation strategies that leverage advanced ML strategies and models, like VLMs, active learning. You Have 2+ years of experience in industrial AI applications involving the creation, maintenance, and evaluation of ML products. Ability to drive the development of new products. Experience in JAX (Preferred), TensorFlow (Preferred), or PyTorch. Functional knowledge of C++ programming. Passion for developing novel ways of measuring the performance of mission-critical ML systems. Experience evaluating the quality of machine learning prediction at scale. We Prefer Background in both computer vision and general machine learning. Experience using and developing distributed systems. Good knowledge of LLM/VLM. 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
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