About the role
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation. This role follows a hybrid work schedule and reports to a Research Director . You will: Lead and manage a team to build large-scale foundation models, powering many offboard and onboard applications for the Waymo Driver Set the technical direction for
the team, develop the execution strategies, and align individual efforts with the overall strategies Develop a collaborative relationship with cross-functional teams across Waymo, including simulation, planner, semantics, and ML infrastructure Establish an inclusive culture for
the team, enabling research innovations and delivering impactful results You have: 2+ years of experience managing medium-size teams Track record in developing team culture and growing people 6+ years experience in deep learning research or applied research Technical experience working with LLMs / VLMs or world models We prefer: Strong background in foundation model related domains, such as pretraining, mid-training, post-training, Transformer modeling, model scaling, self-supervised learning. Experience working with productionizing deep learning models In accordance with Washington state law, we are highlighting our comprehensive