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Open nowPosted 33 days ago

Motion Planning Engineer (PhD, Intern)

DiDi Labs9 open roles

Pay
$46 an hour
Where
San Jose, CA
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Your applicationOpen nowMotion Planning Engineer (PhD, Intern)DiDi Labs · San Jose, CA

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The clock on this job

Early applications get read.

9.5% of postings close within 7 days. Measured by our own scanner across the market. DiDi Labs postings stay open a median of 24 days.

Share of postings closed within
  1. 1.8%1 day
  2. 4.0%3 days
  3. 9.5%7 days
  4. 15.5%14 days
  5. 33.9%30 days
This job: posted 33 days ago

DiDi Labs median: 24 days open

The posting

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.

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

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