Principal Software Engineer, Driver Understanding & Evaluation

The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. We are using state of the art machine learning in our evaluation to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring insights and applicable metrics to teams working on the onboard software and the rider experience. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack.

You will report to our Head of Driver Understanding and Evaluation in a hybrid role.

You will:

• Shape the strategy for machine learning-based evaluation metrics
• Manage large-scale evaluation infrastructure and resource optimization
• Guide Driver Understanding, Simulation, System Engineering, Research and Onboard Software Teams on evaluation strategy
• Champion scientific and statistical rigor in embodied AI applications
• Lead the definition and implementation of important evaluation metrics and reward functions:
• Ensure alignment on evaluation goals and priorities

You have:

• Experience defining and implementing evaluation strategies
• Background in scientific and statistical methods
• Experience in Machine Learning and Deep Learning
• 3+ years of experience leading and scaling large-scale data and evaluation systems
• Mastery of data-driven report writing and technical strategy documentation for executive decision-making
• Technical leadership experience including prior hands-on involvement with the development of large-scale AI or LLM systems

We prefer:

• Mentoring and leadership development experience
• Experience shaping product roadmaps
• Experience with Reinforcement Learning (RL) with Human Feedback
• Expertise in Creating large datasets
• Experience with Large-Scale Global Consumer Products

#LI-Hybrid