Waymo is seeking to develop machine learning solutions to address open problems in autonomous driving, with the goal of safely operating autonomous vehicles in dozens of cities and under all driving conditions.
Requirements
Proficiency in writing and debugging python/numpy-style code
A willingness to work with complexity of globally distributed inference infrastructure
Experience with large scale (many-machine) training infrastructure and techniques for inference with large models such as model sharding/tensor-parallel
Reinforcement Learning infrastructure experience
Large scale distributed inference experience
Responsibilities
Participate in Waymo’s foundation model post-training and evaluation
Develop cutting edge RL and Distillation techniques for Autonomous Vehicle Trajectory Planning
Integrate emerging research from the broader AI community into Waymo’s internal infrastructure, conducting rigorous ablations to identify and scale the most promising methods
Collaborate with other teams to share techniques developed in the AI Foundations teams to other teams at Waymo
Integrate Waymo’s multimodal models into simulators of different levels of fidelity
Other
Bachelor degree in Computer Science, similar technical field of study, or equivalent practical experience
