Staff/Principal AI Transformation Engineer

DiDi Autonomous Driving is seeking a Staff or Principal AI Transformation Engineer to lead its company-wide transition to an AI-native architecture. The role will design and scale AI infrastructure, embed with autonomous driving engineering teams to deploy production-ready AI capabilities, optimize LLM operations, and guide the technical roadmap.

Responsibilities:

• AI Infrastructure & Platform Architecture: Spearhead the evaluation, selection, and deep integration of frontier LLM ecosystems (e.g., Llama, Hugging Face) and commercial AI platforms. Own the architectural design of our unified, distributed AI platform spanning complex data processing, model training, inference pipelines, and evaluation frameworks
• Forward Deployed Execution: Embed directly with core autonomous driving teams (Perception, Prediction, Planning & Control, and Simulation) via the FDE model. Pinpoint engineering bottlenecks, eliminate friction, and translate complex AI capabilities into production-ready internal ecosystems (e.g., AI DevOps, AI Copilots)
• LLMOps / MLOps Orchestration & Optimization: Design and implement highly resilient, scalable automation pipelines for LLM deployment, monitoring, and continuous feedback loops. Optimize GPU cluster utilization, minimize inference latency, and maximize throughput across large-scale production environments
• Technical Roadmap & Vision: Keep a strong pulse on breakthrough trends in AGI and systems engineering. Act as a "super-connector" between external technological innovations and internal systems, ensuring our AI infrastructure maintains a 1-3 year competitive edge