Advancing the future of autonomous driving technology by developing the metrics and evaluation frameworks that ensure the safety, performance, and readiness of self-driving systems.
Requirements
- Proficiency in Python and SQL for data analysis.
- Strong background in statistical methods (e.g., A/B testing, confidence intervals, regression).
- Experience designing metrics to evaluate complex systems (e.g., robotics, autonomous systems, or large-scale software).
- Experience with machine learning (e.g., model evaluation, feature engineering).
- Familiarity with big data tools (Spark, Hadoop, MapReduce).
- Knowledge of traffic regulations or automotive safety standards (e.g., NHTSA).
Responsibilities
- Analyze data from real-world and simulated autonomous vehicle experiments to evaluate system performance.
- Develop and refine quantitative metrics (both rule-based and ML-driven) to assess driving behavior, safety, and passenger comfort.
- Apply statistical inference and hypothesis testing to validate the sensitivity and reliability of metrics.
- Collaborate with autonomy software, simulation, and safety teams to prioritize improvements based on data-driven insights.
- Build scalable data pipelines to automate metric computation and reporting.
- Review driving logs and participate in test rides to ground analyses in real-world performance.
Other
- 2+ years of experience in data science, applied statistics, or metrics development.
- Ability to communicate technical findings to cross-functional stakeholders.
- Candidates are required to be authorized to work in the U.S.
- The employer is not offering relocation sponsorship, and remote work options are not available.
