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++ 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
Similar Jobs
.png){kind=logo}
What We Do
DiDi Global Inc. (NYSE: DIDI) is the world’s leading mobility technology platform. It offers a wide range of app-based services across Asia-Pacific, Latin America and Africa, as well as in Central Asia and Russia, including ride hailing, taxi hailing, chauffeur, hitch and other forms of shared mobility as well as auto solutions, food delivery, intra-city freight and financial services.
DiDi provides car owners, drivers and delivery partners with flexible work and income opportunities. It is committed to collaborating with policymakers, the taxi industry, the automobile industry and the communities to solve the world’s transportation, environmental and employment challenges through the use of AI technology and localized smart transportation innovations. DiDi strives to create better life experiences and greater social value, by building a safe, inclusive and sustainable transportation and local services ecosystem for cities of the future.
