Waymo
Software Engineer, Applied Machine Learning
Waymo, Mountain View, California, us, 94039
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.In this hybrid role, you will report to a Staff Engineering Manager within Behavior.
You will:
Work with a creative team of people who ensure that the behavior of our cars is safe, smooth, and predictable to other road users, which includes gracefully handling many complex situations involving social aspects (merging, negotiating narrow roads), while dealing with noisy, uncertain, and incomplete information.Frame the open-ended real-world problems into well-defined ML problems; apply deep learning, reinforcement learning, imitation learning to these problems; scale them to Google-sized data pipelines; and refine them to run in real-time on the cars.
You have:
BS in Computer Science, ML, Robotics, similar technical field of study, or equivalent practical experience5+ years of experience solving problems using Machine Learning with Tensorflow or equivalent tools and integrating ML in a production systemExperience evaluating ML-based systems
We prefer:
Experience applying machine learning to solve motion planning or related robotics problemsPhD in Computer Science, ML, RoboticsExperience with Deep Neural Networks or Regression Models
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You will:
Work with a creative team of people who ensure that the behavior of our cars is safe, smooth, and predictable to other road users, which includes gracefully handling many complex situations involving social aspects (merging, negotiating narrow roads), while dealing with noisy, uncertain, and incomplete information.Frame the open-ended real-world problems into well-defined ML problems; apply deep learning, reinforcement learning, imitation learning to these problems; scale them to Google-sized data pipelines; and refine them to run in real-time on the cars.
You have:
BS in Computer Science, ML, Robotics, similar technical field of study, or equivalent practical experience5+ years of experience solving problems using Machine Learning with Tensorflow or equivalent tools and integrating ML in a production systemExperience evaluating ML-based systems
We prefer:
Experience applying machine learning to solve motion planning or related robotics problemsPhD in Computer Science, ML, RoboticsExperience with Deep Neural Networks or Regression Models
#J-18808-Ljbffr