Staff Software Engineer, Machine Learning, Planner Selection
About this role
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 Waymo Strategic Selection team is responsible for the critical, real-time decision-making systems that guide the Waymo Driver through complex urban environments. Operating on a horizon of approximately 60 seconds into the future, this team bridges the gap between high-level routing and immediate tactical maneuvers, ensuring safe, comfortable, and efficient trajectories. In this role, you will focus on developing generalized ML models capable of handling a wider range of complex driving situations.
In this role, you will report into a TLM of Planner Technology.
You will:
- Investigate driving behavior issues from logs and understand the root cause
- Improve performance of the state of the art ML models in Planner
- Develop foundational frameworks that help advancement of the Waymo Driver's capabilities.
- Expand the impact of ML models while preserving interpretability and behavioral guarantees
- Directly contribute to solving some of the most challenging driving situations in the long tail.
You have:
- Masters or PhD degree in Computer Science, Machine Learning or a similar discipline.
- Proficiency in C++ or Python
- Experience with Machine Learning models in production systems
We prefer:
- AV or Robotics experience
- 8+ years of Software Engineering experience in complex systems
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.
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You'll be redirected to waymo's official application page on Greenhouse.