Waymo is looking to solve the problem of ensuring the safety and reliability of autonomous vehicles by developing and evaluating ML-heavy systems
Requirements
- Proven expertise using advanced statistical methods (e.g., ML models, hypothesis testing, causal analysis)
- Demonstrated knowledge of Python/SQL/R data analysis libraries and packages
- Ability to interpret and work with data in the presence of ambiguity (e.g., confounding factors, data sparsity or quality challenges)
- Experience solving problems related to Autonomous Driving
- Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction
- Hands-on experience with Google infra tools like PLX, Borg, GCL, etc
Responsibilities
- Develop safety evaluation frameworks that are critical to ML model improvements
- Design and implement robust data analysis pipelines and validation frameworks
- Develop and apply statistical methods and ML models to analyze historical/simulation data and assess safety performance
- Collaborate with cross-functional teams like Simulation and Planning to ensure comprehensive safety evaluation across the autonomous driving system
Other
- PhD in a quantitative field (IE Statistics, Mathematics, Physics)
- 7+ years of industry experience solving large-scale complex problems
- Ability to take ambiguous and complex business requirements and propose a technical solution
- Participation in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements
