Waymo is looking to solve the problem of rigorous performance evaluation of the Waymo Driver to scale its ride hailing service and achieve its audacious goals, specifically in the areas of safety, compliance, and driving and service quality.
Requirements
- Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models
- Demonstrated knowledge of Python/SQL/R data analysis libraries and packages
- Experience solving problems related to Autonomous Driving or Ride Hailing
- Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction
- Familiarity with state-of-the-art simulation technology
- Experience with statistical models and developing metrics and measurement frameworks
Responsibilities
- Develop evaluation frameworks for autonomous vehicle performance, for large-scale ML models, and for the quality of simulation.
- Develop new metrics, interpret trends, and investigate anomalies in data from simulation and on-road driving.
- Develop novel statistical methods to handle unique aspects of AV data; e.g. rate estimation with rare events, combining real and synthetic data, etc.
- Frame and solve ambiguous problems, derive data-driven conclusions, and communicate findings to senior stakeholders.
- Collaborate with Product and Engineering partners developing the Waymo Driver and Waymo’s simulation software; facilitate deployment readiness decisions for both products.
Other
- Degree in a quantitative field (e.g. Statistics, Mathematics, Physics)
- 3+ years of industry experience solving data science problems or a PhD in a quantitative field
- Ability to communicate findings to senior stakeholders
- Collaboration with Product and Engineering partners
- Travel requirements not specified
