DiDi
DiDi is a mobility technology platform offering app-based ride hailing, taxi hailing, shared mobility, food delivery, and intra-city freight to consumers and businesses across Asia Pacific, Latin America, and other markets. It connects riders with drivers and couriers and provides vehicle, energy, and insurance-related services, earning transaction commissions and service fees. DiDi launched an autonomous driving unit in 2016, which became the independent DiDi Autonomous Driving in 2019 to develop Level 4 technology for its network.
Open Positions at DiDi
7 open positions
Join DiDi Autonomous Driving as a Motion Planning Engineer Intern and develop planning algorithms for Level 4 autonomous vehicles. You will work on behavioral planning, trajectory optimization, and safe motion generation for complex driving scenarios.
Lead AI infrastructure performance, inference optimization, deployment, and resource scheduling for autonomous-driving models across vehicle-side and cloud environments. The role bridges deep learning algorithms with real-time embedded systems to deliver low-latency, reliable AI execution.
Lead the architecture and evolution of infrastructure powering a Level 4 autonomous-driving software stack, spanning middleware, compiler and build systems, toolchains, and large-scale simulation. This technical leadership role focuses on low-latency performance, platform stability, developer productivity, and embedded onboard systems.
Develop core behavioral planning and motion-planning systems that enable Level 4 autonomous vehicles to navigate safely and intelligently. The role spans high-level decision-making, trajectory optimization, geometry, and velocity planning.
Lead DiDi Autonomous Driving’s company-wide shift to an AI-Native architecture by designing and implementing large-scale LLM, ML, and distributed AI infrastructure. This hands-on Staff/Principal role combines enterprise AI transformation, systems architecture, platform engineering, and deep optimization of training and inference workloads.
Develop core motion-planning and decision-making software that enables autonomous vehicles to navigate safely, smoothly, and intelligently in complex environments. The role spans behavioral reasoning, trajectory optimization, geometry, and velocity planning.
Develop the map fusion, perception integration, and motion planning software that enables Level 4 autonomous vehicles to navigate safely. The role combines robotics algorithms, deep-learning model deployment, and high-performance C++ systems engineering.