Waymo-posted 10 days ago
Full-time • Mid Level
Hybrid • San Francisco, CA

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 Perception team at Waymo builds technology that powers the Waymo Driver. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We conduct research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling software engineers like you to develop multi-modal models and techniques at scale. Our mission is to build a stable foundation for a high-level Perception pipeline and the overall self-driving system. We act as the crucial interface between Waymo's hardware teams and the rest of the self-driving engineering organization, defining sensor requirements, providing critical feedback to hardware teams, and abstracting away system complexities. In this hybrid role, you will report to a Technical Lead Manager.

  • Triage logged driving events to establish root cause, and work with cross functional teams to drive resolution
  • Develop tools and methodologies to improve and automate the triage process, to get fast and accurate performance statistics using an automated system
  • Evaluate new hardware specifications and changes, and assess the impact on the autonomous vehicle performance
  • Develop simulation tools for new sensor emulation, and simulating autonomous vehicle performance with sensor impairments and injected faults
  • Support sign-off process for all stages of sensing system development and software releases.
  • Present results at milestone sign-off reviews
  • Develop new methodologies and processes for assessing autonomous vehicle performance
  • BS in Computer Science, Robotics, similar technical field of study, or equivalent practical experience
  • Experience with sensor data processing (Lidar, camera, or Radar)
  • 2+ years of experience in industrial AI applications involving the creation, maintenance, and evaluation of ML products
  • Strong experience programming in C++ with robust and efficient code
  • MS or PhD in Computer Science, Robotics, similar technical field of study, or equivalent practical experience
  • Experience with autonomous vehicles (L4) or ADAS systems (L2/L3)
  • Strong software architecture skills
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