Staff/Principal Forward Deployed Engineer

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. DiDi Autonomous Driving is dedicated to advanced AD R&D, product application, and business expansion.

Responsibilities

• Spearhead the evaluation, selection, and deep integration of frontier LLM ecosystems and commercial AI platforms
• Own the architectural design of a unified, distributed AI platform for data processing, model training, and inference
• Embed with core autonomous driving teams to eliminate engineering bottlenecks and translate AI capabilities into production ecosystems
• Design and implement scalable automation pipelines for LLM deployment, monitoring, and continuous feedback loops
• Optimize GPU cluster utilization, inference latency, and throughput across large-scale production environments
• Act as a technical connector between external technological innovations and internal systems

Requirements

• Proven technical leadership in designing complex, system-level architectures
• Proficiency in C++, Python, Java, or JavaScript
• Experience leading large-scale corporate AI-native transformations or building enterprise-grade AI/ML platforms
• Hands-on expertise with PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, or Megatron-LM
• Deep experience in distributed LLM training/inference optimization and large-scale compute cluster operations
• Ability to drive diverse engineering teams toward an AI-first paradigm through technical authority

Preferred Qualifications

• Familiarity with autonomous driving algorithms (Perception, Planning, Control, Simulation) or robotics
• 8-10+ years of professional engineering depth in systems software or cloud infrastructure
• Experience building custom AI Copilot applications or autonomous Multi-Agent Frameworks
• Active contributor to the tech community (open-source, technical papers, or industry speaking)