Motion Planning Engineer (PhD, Intern) New San Jose, CA

Didi Labs; San Jose (CA); Hybrid; USD 52,000 - 74,000; Full time

Benefits offered by this job

Intern benefits

Ongoing program

Job summary

DiDi Autonomous Driving seeks a motivated PhD graduate to advance planning capabilities for autonomous vehicles in a hands-on internship in San Jose. You will apply algorithm design and system integration to strengthen behavioral planning, trajectory optimization, and multi-agent coordination.

You will collaborate with Perception, Prediction, and Control teams to build a robust autonomy stack, deliver safe and smooth trajectories, and work with real-world data and simulation.

Qualifications

• PhD in Robotics, Computer Science, Electrical Engineering, or related field.
• Research or internship in motion planning, behavioral planning, trajectory optimization, or multi-agent modeling.
• Publications in top-tier conferences (e.g., RSS, ICRA, IROS, CVPR, NeurIPS, CoRL).
• Hands-on experience in C++ for real-time algorithms.

Responsibilities

• Implement novel solutions for Behavioral Planning, enabling high-level decisions for lane changes, merges, and multi-agent interactions.
• Design and optimize motion planning algorithms with geometry-based path reasoning and context-aware speed planning.
• Develop core geometry and velocity planning systems for safe, comfortable trajectories across diverse scenarios.
• Model complex driving environments and agent behaviors to support planning under uncertainty.
• Formulate cost functions and optimization frameworks balancing safety, comfort, and efficiency.
• Analyze, test, and debug system performance using simulation and real-world data.
• Collaborate with researchers across Perception, Prediction, and Control to integrate the autonomy stack.

Skills

Motion planning

Behavioral planning

Trajectory optimization

Multi-agent modeling

C++

Publications

Education

PhD in Robotics

PhD in Computer Science

PhD in Electrical Engineering

Tools

Python

Job description

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

We 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

• 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.
  

Qualifications

• 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++ 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 willalso be eligible for Intern benefits.

Applications are accepted on an ongoing basis. This posting is for an existing vacancy.

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