Senior Software Engineer, Quantitative Evaluations

The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you!

This role follows a hybrid work schedule and reports to a Senior Engineering Manager.

You will:

• Develop novel methodologies and metrics to measure simulation realism across multiple simulator technologies (e.g., agent behavior, sensor rendering, environmental effects).
• Design scalable and efficient platforms and pipelines for measuring simulation realism across massive datasets.
• Research and implement systems that can guide simulator development priorities.
• Collaborate with world-class engineering and research teams who develop and use large-scale ML models to enhance simulator fidelity.
• Play an important role in a collaborative engineering team dedicated to building a high-fidelity simulator that directly powers the safety validation and performance evaluation of the Waymo Driver.

You have:

• MS in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 5+ years of industry experience in software development.
• Software Engineering Fundamentals:
  • Proficiency in programming in Python or C++, including experience with relevant libraries for data handling and computation (e.g., NumPy, Pandas for Python).
  • Experience with SQL for data querying and analysis.
  • Experience with software design principles, coding best practices, testing methodologies, and version control software.
• Quantitative Application & Metric Development:
  • Identify potential system performance or realism gaps (e.g., from specific examples or initial data exploration) and create data-driven approaches to investigate them.
  • Experience designing, implementing, and interpreting quantitative analyses or metrics to systematically evaluate system behavior and validate hypotheses (using concepts such as distributions, confidence intervals, etc.).
  • Demonstrated experience taking quantitative findings through to implementation, resulting in productionized metrics, automated evaluation tools, or improvements to validation systems.
• Software Development for Data/Evaluation Pipelines:
  • Experience building software pipelines for data processing, system evaluation, or metric computation, in the context of large-scale systems.

We prefer:

• Demonstrated expertise and influence in designing quantitative evaluation methodologies and building scalable data processing/evaluation infrastructure.
• Experience navigating complex technical and product landscapes, defining technical strategy, and creating roadmaps.
• Experience with simulation systems, robotics, or autonomous vehicles.

#LI-Hybrid