Technical Lead Manager, Planner Research
Waymo
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, you will report to a Director of Research.
You will:
- Plan and implement an Machine Learning driven AV planner research agenda
- Incorporate and extend research in robotics and machine learning to promote the state-of-the-art for high-level planning for autonomous vehicles, with advanced techniques in foundation modeling, reinforcement learning and search
- Manage and technically lead a team of research scientists as they grow in their careers
- Partner across our organizations to land tech in production
- Publish work at top-tier academic venues
You have:
- Bachelor's degree Computer Science, Machine Learning, Robotics, similar technical field of study, or equivalent practical experience
- 10+ years of experience developing or doing research in deep learning-based systems for robotics, involving dataset, evaluation, and model design.
- 5+ years of experience managing a team
- Proficiency in Python
- Hands-on experience developing modern deep learning architectures and training
We prefer:
- Masters or PhD, preferably in Machine Learning domain
- Publications in top-tier conferences or leading open source projects in the related fields
- 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
