Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.
The mission of the Waymo Applied Research team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of the 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.
This hybrid role will report to a Director of Research.
In this role you'll:
- Plan and execute an ambitious ML-driven AV planner research agenda
- Incorporate and extend cutting edge research in robotics and machine learning to advance the state of the art for high level planning for autonomous vehicles, via advanced techniques in foundation modeling, RL and search.
- Manage and technically lead a team of research scientists as they grow in their careers
- Partner within and across organizations to land disruptive and innovative tech in production
- Publish work at top-tier academic venues
At a minimum, we'd like you to have:
- Bachelor's degree Computer Science, Machine Learning, Robotics, similar technical field of study, or equivalent practical experience
- Proven experience developing or doing research in deep learning-based systems for robotics, involving dataset, evaluation, and model design.
- Proficiency in Python
- Strong hands on experience developing modern deep learning architectures and training
It's preferred if you have:
- Masters or PhD, preferably in Machine Learning domain
- Track record of publications in top-tier conferences or leading open source projects in the related fields
- Strong hands-on SWE skills, able to implement or extend large scale data and evaluation pipelines
- Proficiency in C++
- Proficiency in one or more deep learning frameworks
- Experience in AV planning and related research
#LI-Hybrid
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