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Staff Machine Learning Engineer, Prediction & Planning, System ArchitectureWaymo • Mountain View, California, United States
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Staff Machine Learning Engineer, Prediction & Planning, System Architecture

Waymo
  • US
    Mountain View, California, United States
  • US
    Mountain View, California, United States
Jetzt Bewerben

Über

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.
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 hybrid 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 7+ 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
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range $251,000$310,000 USD Required
Preferred
Job Industries
Other
  • Mountain View, California, United States

Sprachkenntnisse

  • English
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