About the role#
DiDi Autonomous Driving is seeking a PhD student to join the team as a Motion Planning Intern. This role focuses on applying research expertise in robotics and autonomous systems to develop next-generation planning capabilities for autonomous vehicles. Top-performing interns may be considered for a full-time position upon completion of the program.
What you'll do#
- Implement novel solutions for Behavioral Planning, including decision-making for lane changes, merges, yields, and multi-agent interactions.
- Design and optimize motion planning algorithms that integrate geometry-based path reasoning and context-aware speed reasoning.
- Develop and improve core geometry and velocity planning systems to ensure safety and comfort.
- Model complex driving environments and agent behaviors to support planning under uncertainty.
- Formulate cost functions and optimization frameworks to balance safety, comfort, and efficiency.
- Analyze, test, and debug system performance through simulation and real-world data.
- Collaborate with Perception, Prediction, and Control teams to ensure an integrated autonomy stack.
What you'll need#
- Recently completed or soon-to-complete PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
- Research or internship experience in motion planning algorithms, behavioral planning, decision-making under uncertainty, or trajectory optimization.
- Proven research ability demonstrated by publications in top-tier conferences such as RSS, ICRA, IROS, CVPR, NeurIPS, or CoRL.
- Hands-on experience in C++ for implementing complex, real-time algorithms.
- Excellent analytical and communication skills with a collaborative mindset.
Location & details#
- Location: San Jose, California
- Modality: On-site
- Term: Rolling
- Compensation: $46 per hour
- Employment Type: Full-time internship
