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Staff Software Engineer, Machine Learning, Predictive Planning
Staff Software Engineer, Machine Learning, Predictive Planning
The Staff Software Engineer, Machine Learning, on the Predictive Planning team at Waymo will design, implement, and evaluate state-of-the-art generative models for autonomous vehicle planning and prediction. This role involves developing next-generation, ML-powered systems and translating real-world driving challenges into well-defined machine learning problems using cutting-edge techniques like foundation models and reinforcement learning. The engineer will write high-quality, scalable code and collaborate with researchers and product managers to deliver safe and smooth planning behaviors.
About the role
About Waymo
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.
About the Predictive Planning Team
The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver’s behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks. These models enable the autonomous vehicle to navigate complex environments safely and efficiently.
Responsibilities
- Design, implement, and evaluate state-of-the-art generative models for autonomous vehicle planning and prediction
- Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo’s business
- Translate open-ended, real-world driving challenges into well-defined machine learning problems, applying cutting-edge techniques, including foundation models and reinforcement learning
- Write high-quality, scalable, and thoroughly tested code to bring cutting-edge research into production
- Partner with world-class researchers, engineers, and product managers to deliver safe and smooth planning behaviors, and publish findings at top-tier academic venues
Qualifications
You have:
- PhD in Computer Science, Machine Learning, Robotics, a related technical field, or equivalent practical experience
- A proven track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP)
- Demonstrated impact on the broader ML community through influential research, widely adopted open-source projects, or significant industry contributions
- Hands-on expertise with modern deep learning frameworks, for example JAX or PyTorch
- Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities
We prefer:
- Specialized research experience in deep learning, reinforcement learning, causal reasoning, or foundation models
- Prior industry experience (e.g. internships) in applied ML research or software development
- Domain expertise in solving motion planning, prediction, or related robotics problems
- Hands-on experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments
Skills
Machine Learninggenerative modelsDeep Neural Networksfoundation modelsReinforcement LearningJaxPyTorchPythonC++Causal ReasoningMotion PlanningRoboticsML based Systems