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Salary
≈ $118k – $231k per year (Estimated)
Location
In office (San Jose)
Seniority
Middle · 3+ years exp
Visa
H-1B filings in 12 months: 31 · for this role: 29 · green card filings: 12
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on May 2, 2020. WeRide scores B on the Alion truth index.

Overview
Company
Impact
Profile match
WeRide is an autonomous driving technology company that develops self-driving systems from Level 2 to Level 4, including robotaxis, robobuses, robosweepers and robovans. It operates commercial services in China, the Middle East and Southeast Asia and is listed on NASDAQ and the Hong Kong Stock Exchange. The company is headquartered in Guangzhou, China.

WeRide.ai Silicon Valley team is looking for Motion Planning Engineers who enjoy having their software make critical decisions rather than just “process” or “display” data. We need people unafraid of crafting motion planning systems to make great decisions, every time, in all conditions.

What you will do:

  • Building/Integrating software and algorithms for path planning, behavioral planning and vehicle control
  • Developing/Implementing/Evaluating/Launching algorithms in Robotic motion planning (e.g., A*, CC-RRT), vehicle modeling and kinematics

Requirements:

  • BS/MS/PhD degree in a relevant field of study (e.g., Computer Science, Computer Engineering)
  • Skilled in numerical optimization techniques (e.g., nonlinear constrained optimization) or skilled in AI or Robotics
  • Proven ability to produce computationally efficient software that can meet real-time requirements
  • 3+ years experience in motion planning, AI, or autonomy for real-world applications

Plus:

  • Hands-on experience in robotic and/or vehicle system design and implementation
  • Knowledge of ROS
  • Knowledge of Linux, and development on Linux systems
  • Experience working in an automotive, aerospace, environments
  • Experience in writing safety-critical code
  • SLAM / Probabilistic Filtering experience
  • Experience in doing reinforcement learning
  • Experience with real-time sensor fusion (e.g. IMU, lidar, camera, odometry, radar)
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