Job description

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 junior or skilled Software Engineer to join our team and develop the core decision-making and motion planning systems for our autonomous vehicles. In this role, you will be responsible for creating the algorithms that enable smooth, safe, and intelligent navigation in complex environments. You will tackle challenges across the full motion planning stack, from high-level behavioral reasoning to low-level trajectory optimization. Responsibilities Design and implement the core Behavioral Planning logic that determines the vehicle's high-level actions (e.g., lane changes, merges, yields, and interactions with other agents). Develop and optimize the motion planning algorithms that execute behavioral decisions, integrating Geometry Reasoning (path) and Speed Reasoning (velocity) into a cohesive trajectory. Architect and enhance the geometry system for generating geometrically feasible and compliant paths. Architect and refine the velocity system for generating context-aware, comfortable, and safe velocity profiles. Model complex driving scenarios and agent interactions to create a robust world model for the behavioral planner. Design different costs for trajectory ranking to trade off ETAs, comfort and safety of the vehicle behaviors. Conduct in-depth analysis, testing, and debugging of the system's performance in various scenarios, leading root cause investigations. Collaborate with Prediction, Perception, and Control teams to ensure a seamless flow from environmental understanding to physical vehicle motion. Qualifications B.S./M.S. in Computer Science, Robotics, or a related field. E xperience in autonomous systems, robotics, or automotive software development. Strong proficiency in C++ and Python for implementing complex, real-time algorithms. Solid understanding of robotics fundamentals, including decision-making, motion planning, control theory , trajectory ranking, search and optimization algorithms etc . Related experience in one or more of the following: behavioral planning, motion planning, behavior and world environment reasoning, trajectory ranking and cost design . Preferred Qualifications PhD or internship experience related to robotics planning system designs . Knowledge of vehicle dynamics and longitudinal/lateral control systems. Solid understanding of machine learning principles , reinforcement learning and related algorithms. The base salary range for this full-time position is $129,189-$214,776 annually in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on v.didi.cn

Requirements

Must-haves

Design and implement the core Behavioral Planning logic that determines the vehicle's high-level actions (e.g., lane changes, merges, yields, and interactions with other agents).
Develop and optimize the motion planning algorithms that execute behavioral decisions, integrating Geometry Reasoning (path) and Speed Reasoning (velocity) into a cohesive trajectory.
Architect and enhance the geometry system for generating geometrically feasible and compliant paths.
Architect and refine the velocity system for generating context-aware, comfortable, and safe velocity profiles.
Model complex driving scenarios and agent interactions to create a robust world model for the behavioral planner.
Design different costs for trajectory ranking to trade off ETAs, comfort and safety of the vehicle behaviors.
Conduct in-depth analysis, testing, and debugging of the system's performance in various scenarios, leading root cause investigations.
Collaborate with Prediction, Perception, and Control teams to ensure a seamless flow from environmental understanding to physical vehicle motion.
B.S./M.S. in Computer Science, Robotics, or a related field.
E xperience in autonomous systems, robotics, or automotive software development.
Strong proficiency in C++ and Python for implementing complex, real-time algorithms.
Solid understanding of robotics fundamentals, including decision-making, motion planning, control theory , trajectory ranking, search and optimization algorithms etc .
Related experience in one or more of the following: behavioral planning, motion planning, behavior and world environment reasoning, trajectory ranking and cost design .

Nice-to-haves

PhD or internship experience related to robotics planning system designs .
Knowledge of vehicle dynamics and longitudinal/lateral control systems.
Solid understanding of machine learning principles , reinforcement learning and related algorithms.
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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonmachine learning

Platform: greenhouse
Effort: quick