Program Manager, ML Data Flywheel

<div class="content-intro"><p>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.</p></div><p>The Labeling Data Program Org owns the execution and creation of curated labeled datasets which are critical for training and evaluation of ML models that power the Waymo Driver.</p> <p>As a Program Manager in this team, you will be the operational backbone of our machine learning initiatives. You will own and drive the complex, cross-functional programs that deliver high-quality data—the lifeblood of our models. You will orchestrate the end-to-end data lifecycle, from defining requirements for new datasets and tooling to scaling data pipelines and ensuring our ML teams have the resources they need to innovate. This is a high-impact role for a technical, detail-oriented leader who thrives on turning ambiguous data needs into tangible, scalable solutions.</p> <p><strong>You will:</strong></p> <ul> <li><strong>Drive the ML Flywheel:</strong> Lead the end-to-end lifecycle of ML data, from initial mining and curation to labeling policy definition, validation, and model evaluation. Work cross-functionally to ensure coordination and alignment on objectives and key results.</li> <li><strong>Translate Policy to Code: </strong> Lead the development of sophisticated labeling policies for complex AV domains (e.g., behavior prediction, long-tail edge cases). Convert ambiguous ML quality problems into precise, scalable annotation policies and data taxonomies. </li> <li><strong>Build Evals Metrics:</strong> Design and implement ML evaluation frameworks. Identify key data-centric drivers of model performance and create the metrics that track ML quality at the data level.</li> <li><strong>Cross-Functional Leadership</strong>: Communicate effectively with technical and non-technical audiences at various levels of seniority, including producing analytical write-ups, dashboards, and data visualizations to convey your findings and recommendations to our team and cross-functional stakeholders</li> <li>Influence ML data selection strategies (active learning, hard-mining) to ensure we are labeling the most impactful data to maximize ROI from the labeling effort</li> </ul> <p> </p> <p><strong>You have:<br></strong></p> <ul> <li>8+ years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.</li> <li>Deep understanding of the ML data lifecycle: labeling, taxonomy design, quality control, and data curation.</li> <li>Experience with ML Data Flywheel and working understanding of ML development life cycle (e.g., model deployment,model evaluation, data processing, debugging, fine tuning).</li> <li>Background in leading and managing complex programs that span across organizations and functions, with specific experience in Machine Learning data annotation or Human-in-the-Loop initiatives.</li> <li>Strong ability to thrive in a dynamic environment, demonstrating comfort and effectiveness when dealing with ambiguity.</li> <li>Ability to quickly learn and implement new concepts and utilize proprietary tools. Strong understanding of driving rules and regulations.</li> </ul> <p><strong> </strong></p> <p> </p> <p><strong>We prefer:</strong></p> <ul> <li>Experience with scripting language, machine learning tools, techniques and systems (in ... (truncated, view full listing at source)