Motion Planning Engineer (PhD, Intern)
Quick Summary
Motion planning algorithms (optimization, sampling,
DiDi's autonomous driving unit was established in 2016 with the mission of developing Level 4 autonomous driving (AD) technology to make transportation safer and more efficient. In August 2019, the unit became an independent company, DiDi Autonomous Driving, dedicated to advanced AD R&D, product application, and business expansion. We believe integrating AD technology into a shared-mobility fleet will generate immense social value. By leveraging DiDi's specialized technology, operational expertise, and integrated ecosystem, we are positioned to build and operate a highly efficient, user-oriented autonomous fleet.
About the Role
~1 min readWe are seeking a motivated PhD graduate with a strong research background in motion planning, robotics, or autonomous systems. In this role, you will apply your expertise in algorithm design and system integration to help develop next-generation planning capabilities for autonomous vehicles.
Responsibilities
~1 min read- →Implement novel solutions for Behavioral Planning, enabling high-level 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 into smooth, safe trajectories.
- →Develop and improve core geometry and velocity planning systems to ensure feasibility, compliance, and comfort across diverse driving scenarios.
- →Model complex driving environments and agent behaviors to create a robust world representation for planning under uncertainty.
- →Formulate cost functions and optimization frameworks that balance safety, comfort, and efficiency in trajectory selection.
- →Analyze, test, and debug system performance through simulation and real-world data, conducting root-cause investigations and proposing enhancements.
- →Collaborate with researchers and engineers across Perception, Prediction, and Control to ensure an integrated, reliable autonomy stack.
Requirements
~1 min read- Recently completed or soon-to-complete PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
- Research or Internship experience in one or more of the following:
- Motion planning algorithms (optimization, sampling, graph/search-based methods)
- Behavioral planning and decision-making under uncertainty
- Trajectory optimization and control
- Multi-agent interaction modeling
- Proven research ability demonstrated by publications in top-tier conferences (e.g., RSS, ICRA, IROS, CVPR, NeurIPS, CoRL).
- Hands-on experience in C++ and Python for implementing complex, real-time algorithms.
- Excellent analytical and communication skills, with a collaborative mindset.
- For Internship Applicants: This role offers a clear pathway, with top-performing interns receiving the opportunity to convert to a full-time engineer upon successful completion of the program.
The hourly rate for the Intern position in the selected city is $46. Interns will also be eligible for Intern benefits.
Applications are accepted on an ongoing basis. This posting is for an existing vacancy.
I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on https://v.didi.cn/AQnxlBa
Location & Eligibility
Listing Details
- Posted
- July 1, 2026
- First seen
- July 1, 2026
- Last seen
- July 4, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 60%
- Scored at
- July 1, 2026
Signal breakdown
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