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.
This role is part of Waymo's Perception Development Foundations (PDF) team. The PDF team's mission is to accelerate improvements to Waymo's Perception system by providing teams with cutting-edge Data, Model Development tools, and Evaluation frameworks. We focus on removing toil, increasing automation, and enhancing how models use data and how we measure performance.
In this hybrid role, you will report to a director of engineering.
You will:
Define and own the overarching vision and multi-year strategy for determining the size, composition, and collection methods for datasets used in Perception model training and evaluation.
Drive the design and organizational adoption of frameworks to estimate data needs based on model performance, scaling laws, generalization goals, and a deep understanding of the diversity in new geographies.
Define and refine strategies for Perception evaluation datasets, ensuring they provide sufficient coverage and statistical power to measure progress and de-risk new deployments.
Collaborate closely with Perception engineers, ML researchers, the Labeling organization, and Operations teams to translate strategic recommendations into actionable labeling plans.
Analyze existing data sources to identify structural gaps, biases, and opportunities for more efficient data utilization.
Establish and champion data-driven best practices for dataset design and data quality within the Perception organization, driving operational maturity.
Establish the impact of the Data Science function within Perception as a hands-on IC, followed by building a small team.
You have:
BS/MS and 10+ years of industry experience, or PhD + 8 years of industry experience in Statistics, Mathematics, Physics, Economics, Engineering, Computer Science, or a related quantitative field.
8+ years of experience using analytics, statistical modeling, and machine learning to solve complex product, business, or autonomous systems problems.
5+ years of experience in coding (e.g., Python, R, SQL), querying databases, and statistical analysis.
Proven ability to lead and deliver on highly ambiguous, high-impact technical projects in a self-directed environment.
Strong communication and collaboration skills, with a track record of influencing cross-functional teams and senior leadership.
We prefer:
Experience applying statistical and machine learning techniques to large-scale datasets.
6+ years of experience leading data analytics or data science initiatives, including defining strategy, roadmaps, and building functions from the ground up.
Deep experience with data collection strategies, experimental design, sampling methodologies, and causal inference.
A track record of mentoring other Data Scientists and driving adoption of new methods across an entire organization.
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.