DiDi Labs
Motion Planning Engineer (PhD, Intern)
About this role
DiDi Autonomous Driving seeks a PhD graduate to develop motion planning algorithms for Level 4 autonomous vehicles. You'll design behavioral and trajectory planning systems, optimize cost functions, and collaborate across the autonomy stack to enable safe, efficient autonomous driving.
What you'll do
- Implement behavioral planning solutions for lane changes, merges, yields, and multi-agent interactions
- Design and optimize motion planning algorithms integrating geometry-based path and context-aware speed reasoning
- Develop core geometry and velocity planning systems for feasibility and comfort across driving scenarios
- Model complex driving environments and agent behaviors for robust planning under uncertainty
- Formulate cost functions and optimization frameworks balancing safety, comfort, and efficiency
- Analyze system performance via simulation and real-world data with root-cause investigation
What they're looking for
- Motion planning algorithms (optimization, sampling, graph/search methods)
- Behavioral planning and decision-making under uncertainty
- Trajectory optimization and control
- C++ implementation of real-time algorithms
- Multi-agent interaction modeling
- Analytical and communication skills
- Collaborative problem-solving
- Simulation and real-world data analysis
Benefits
- Pathway to full-time conversion for top-performing interns
- Intern benefits package
- Research-focused role at leading autonomous driving company
- Collaboration with Perception, Prediction, and Control teams
- Access to simulation and real-world testing environment
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DiDi Labs
DiDi Labs develops autonomous driving technology for Level 4 vehicles, focusing on motion planning, behavioral decision-making, map fusion, and robotic simulation systems. The company is hiring software engineers and researchers to build algorithms, trajectory optimization systems, and cloud-based simulation infrastructure that enable safe and intelligent autonomous vehicle navigation.
View all jobs at DiDi LabsLikely interview questions
- Walk us through a motion planning algorithm you developed during your PhD research and how you optimized it for real-world constraints.
- How have you approached the challenge of balancing safety, comfort, and efficiency in trajectory optimization?