Motion Planning Engineer (PhD, Intern) at DiDi Global

About The Company

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 will also be eligible for Intern benefits.

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

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About The Company

About The Role

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 will also be eligible for Intern benefits.