Staff/Principal Forward Deployed Engineer

About the role

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. At DiDi Autonomous Driving, we firmly believe that the future of mobility goes beyond simply "utilizing AI"-it will be fundamentally reimagined and entirely driven by an AI-Native architecture . We are seeking a visionary, highly technical, and mission-driven Staff / Principal Forward Deployed Engineer (FDE) to act as the ultimate catalyst for our company-wide AI transformation. In this strategic, high-impact role, you will combine cutting-edge Large Language Model (LLM) expertise, robust systems architecture design, and a proven track record of enterprise-level AI scaling. You will embed deeply with our core engineering teams to evolve our traditional R&D organization into a truly AI-Native powerhouse.

Responsibilities

• 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.
• Qualifications & Experience
• Cross-Functional Influence: Demonstrated ability to build technical authority, align priorities, and drive diverse engineering teams (Algorithms, Infrastructure, Hardware) toward adopting an AI-first engineering paradigm without relying on formal administrative authority.
• Enterprise AI Transformation: Proven experience leading or heavily contributing to a large-scale corporate "AI-native transformation," or a track record of building enterprise-grade AI/ML platforms from 0 to 1.
• Deep AI Tech Stack Expertise: Thorough hands-on deployment, tuning, and optimization experience with mainstream AI infrastructure tools and frameworks, including but not limited to PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, and Megatron-LM.
• Hardcore AI Infra Experience: Years of deep, practical experience in distributed LLM training/inference optimization and large-scale compute cluster infrastructure & operations (I&O).

Requirements

• Domain Expertise: Familiarity with autonomous driving algorithms (Perception, Planning, Control, Simulation), robotics, physics-based simulation engines, or ultra-large-scale ML training/serving clusters is highly preferred.
• Senior Industry Track Record: 8-10+ years of professional engineering depth in systems software, core cloud infrastructure, or production-grade machine learning platforms.
• Agentic Frameworks & Developer Productivity: Hands-on experience building custom AI Copilot applications, autonomous Multi-Agent Frameworks, or high-tier developer productivity platforms.
• Thriving in Complexity: Proven success steering core project delivery amidst complex business logic, fast-paced/high-pressure environments, or mission-critical systems.
• Technical Influence: An active contributor to the broader tech community (e.g., open-source maintainer/owner, author of high-quality technical blogs/papers, or speaker at premier industry AI/ML conferences).
• The base salary range for this full-time position is $255,000 -$351,0

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