Teams at DiDi

Develop core decision-making and motion-planning systems for Level 4 autonomous vehicles. Responsibilities include behavioral planning, lane changes, merges, path and velocity generation, world modeling, trajectory cost design, optimization, testing, debugging, and root-cause analysis. Collaborate with Prediction, Perception, and Control teams to enable safe, comfortable vehicle motion.

Leads company-wide AI transformation by designing distributed AI platforms for data processing, model training, inference, and evaluation. Embeds with autonomous driving teams to deploy AI DevOps and copilot ecosystems, while building LLMOps/MLOps automation, optimizing GPU clusters, reducing inference latency, and establishing long-term AI infrastructure strategy. The role requires hands-on systems engineering, enterprise AI platform experience, cross-functional technical influence, and deep distributed LLM training and inference expertise.

Lead system safety strategy and deployment readiness for fully autonomous driving systems. Define safety requirements, architectures, release policies, degradation and fallback criteria, verification and validation plans, evaluation metrics, emergency protocols, and operational workflows. Analyze safety incidents, improve system design and test coverage, and collaborate with Software, Product, Operations, and Safety teams to support unmanned deployment, city expansion, and commercial scaling.