<div>Waymo is an autonomous driving technology company with the mission to be the worlds most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The Worlds 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.</div>Within Perception, the Data Refinery team builds the data and evaluation systems to benchmark models and accelerate the ML development cycle. We design the centralized systems and tools for rigorous model quality analysis, debugging, and performance measurement after a model has been trained. Our work provides the fast, actionable feedback loops that shorten the development cycle from days to hours , enabling teams to iterate, improve, and ship better models faster. We collaborate across ML and Infrastructure teams to integrate this standardized evaluation into the core ML lifecycle and help bring new capabilities to the Waymo Driver. In this hybrid role, you will report to an engineering manager. You will: <ul> <li>Design, build, and maintain scalable data pipelines to process many petabytes of complex sensor data, making it ready for efficient model training and evaluation.</li> <li>Develop infrastructure to produce reliable, high-quality datasets for a wide range of ML models, from real-time on-car models to large-scale offboard foundation models.</li> <li>Build and scale a centralized model benchmarking system to provide fast, standardized, and reproducible model quality metrics, reducing the model development cycle from days to hours.</li> <li>Implement tools for deep model quality analysis, including comparative leaderboards and integrated triage/debugging workflows.</li> <li>Automate data quality and validation checks to ensure the integrity, consistency, and trustworthiness of our datasets as we scale to new cities and vehicle platforms</li> <li>Collaborate closely with ML engineers, research scientists, and core infrastructure teams to understand user needs and deliver impactful data and evaluation solutions.</li> </ul>   You have: <ul> <li> C++ programming skills (required), with Python experience </li> <li> 5+ years in ML data engineering, including data pipelines, data curation, data balancing. </li> <li> Experience with the ML development lifecycle, including data engineering, model evaluation, and metric computation. </li> </ul>   We prefer: <ul> <li>Hands-on experience in building large scale data processing or retrieval systems and pipelines: Apache Spark, Apache Beam, Google Cloud Dataflow, AWS Data Pipeline, Faiss/ScaNN, etc.</li> <li>Experience with the end-to-end process of benchmark creation, from defining domain-specific metrics, to curating challenging evaluation datasets, to triaging examples and improving the benchmark.</li> </ul><div><div><div>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. </div><div>Salary Range</div><div>$204,000—$259,000 USD</div></div></div>