About the role
On the Dynamic Agent Interactions (DAI) team at Zoox, you will be dedicated to improving the driving behavior of our autonomous vehicles. DAI handles dynamic interactions with dynamic vehicles and dynamic environments, ensuring our vehicles navigate safely and comfortably through complex scenarios, such as the dense traffic of Downtown San Francisco, Las Vegas, Austin, Miami, and more.
This is a cutting-edge problem, which requires teamwork and close collaboration with experts from Planner, Perception, Prediction, Operations, and more. Together, you will innovate through data-driven ML models and algorithmic enhancements, significantly improving our robot’s ability to handle the most complex driving scenarios on public roads.
Safety is foundational at Zoox, so you will take a measured approach – develop principled modifications, test in simulation, and validate on closed courses before on-road deployment.
In this role, you will:
Develop and execute on the technical roadmap for the DAI’s integration with Scene Understanding and Perception Mapping to deliver end-to-end desired driving behavior in complex dynamic environments.
Lead the design, implementation, and delivery of desired driving behaviors through applied ML.
Serve as a technical leader within the DAI team by contributing to design decisions, fostering our “One Zoox” culture, and maintaining high standards across Planner and ML development.
Leverage our extensive backend tooling to develop validation strategies, define performance metrics, and test changes across many different driving situations.
Qualifications
Bachelor’s or Master’s degree in Computer Science or a related field and 7+ years of experience
Fluency in C++ and Python
Demonstrated ability to create architectural enhancement to complex real-time systems
Experience delivering ML model integration in latency-sensitive systems
Bonus Qualifications
Experience working on the autonomy stack of autonomous robots or vehicles
Experience contributing to the ongoing development of new architecture based on new, state of the art ML research
