Senior Machine Learning Engineer, Predictive Planner, Systems Arch

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.

The system architecture team handles the onboard contract of the model with the system, including kinematics, interfaces and representations. Our team’s mission is to work across the stack, building the best setup for the model to drive. We tackle this through projects in data, modeling, metrics, and the overall planner system.

In this role, you will report to a Technical Lead Manager.

You will:

• Tackle challenging real-world problems with ML and engineering solutions.
• Use state of the art techniques to design and build ML models, deploy them in the real world on production vehicles
• Design and build the necessary architectures, algorithms, pipelines and evaluation systems on Google's extensive data infrastructure
• Collaborate with researchers, product area owners and engineers to develop safe, smooth planning behavior for all road users & deliver product requirements.

You have:

• Bachelors in Computer Science, ML, Robotics, similar technical field of study, or equivalent practical experience
• Hands-on experience with modern deep learning libraries (eg: TensorFlow, JAX, Pytorch)
• Proficient programming skills (eg: Python, C/C++)
• Strong analytical and problem solving skills
• 4+ years of experience in Machine Learning modeling and/or Autonomous Vehicles systems

We prefer:

• MS or PhD in Computer Science, Machine Learning, Robotics, or a related field
• Publications in top-tier conferences such as ICML, NeurIPS,  CVPR, ICCV, ECCV, ICLR, IROS, CoRL, ACL, or EMNLP
• Prior software development or ML research industry experience (including internships)
• General software engineering experience solving motion planning or related robotics problems
• Experience applying or evaluating ML-based systems in production environments
• Experience with performance optimization of deep models, including with respect to specific hardware architectures