At a glance
Build and deploy learned interaction policies for Waymo’s autonomous Driver, using ML, motion planning, and closed-loop simulation to safely handle complex vehicle interactions in production.
Summarized by AI from the original posting
What you'll do
- Design, evaluate, and deploy learned interaction policies
- Develop agent reasoning and motion planning algorithms
- Collaborate across prediction and planning
- Integrate learned models into closed-loop simulation environments
- Benchmark against safety metrics
- Drive transitions from rule-based heuristics to data-driven policies
Requirements
- 01Hands-on experience building ML models
- 02Experience shipping models to production
- 03Cross-functional collaboration skills
- 04Experience building, training, and benchmarking ML systems at scale preferred
- 05Technical leadership experience preferred
Perks
Skills
Full description
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 Vehicle Interaction team tackles critical autonomous driving challenges, directly responsible for modeling agent interactions with other vehicles to advance our mission of safety and building the world's most trusted driver. The team develops agent reasoning and motion planning algorithms to resolve complex interactive scenarios—including lane changes, merges, unprotected maneuvers, and cut-ins. By combining core robotics principles with scalable, production-deployed machine learning models, the team enables the Driver to safely, predictably, and seamlessly navigate dynamic real-world environments.
In this hybrid role, you will report directly to the Technical Lead Manager.
You will:
- Design, evaluate, and deploy learned interaction policies to handle complex navigation and yielding scenarios.
- Collaborate cross-functionally at the intersection of prediction and planning, leveraging large-scale models to solve complex agent interaction problems.
- Integrate learned models into closed-loop simulation environments, benchmark against rigorous safety metrics, and drive seamless transitions to production releases.
- Focus on high-impact product outcomes, making pragmatic engineering decisions to accelerate the shift from rule-based heuristics to scalable, data-driven policies.
You have:
- BS in Computer Science, Machine Learning, Robotics, a related technical field, or equivalent practical experience.
- 5+ years of software engineering experience developing high-performance, efficient C++ code.
- Hands-on experience building ML models, including expertise in learned driving policies (RL/imitation learning), PyTorch or JAX, closed-loop simulation evaluation, and a proven track record of shipping models to production.
- Proven capability to collaborate effectively across cross-functional engineering teams.
We prefer:
- MS or PhD in Computer Science, Machine Learning, Robotics, or a related technical field.
- Demonstrated software engineering expertise in motion planning or related autonomous systems problems.
- Experience building, training, and benchmarking machine learning systems at scale.
- Technical leadership experience guiding engineers or leading small project teams.
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$213,000—$263,000 USD