DiDi Labs

Staff/Principal Forward Deployed Engineer

San Jose, CA · Principal · Full-time

Sponsorship not specified$255k-$351kDetected 11 days ago

JavaScriptPythonJavaC++AlgorithmsCloud PlatformsKubernetesDevOpsMachine LearningPyTorchNLPLLMsLLMOpsMLOpsRoboticsLeadership

About the role

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.
You will embed deeply with our core engineering teams to evolve our traditional R&D organization into a truly AI-Native powerhouse.

Own the architectural design of our unified, distributed AI platform spanning complex data processing, model training, inference pipelines, and evaluation frameworks.
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.
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.
Act as a "super-connector" between external technological innovations and internal systems, ensuring our AI infrastructure maintains a 1-3 year competitive edge.
A proven technical leader who can design complex, system-level architectures while maintaining a fierce passion for writing core code, debugging deep system issues, and optimizing low-level execution paths.

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).
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.

Embed directly with core autonomous driving teams (Perception, Prediction, Planning & Control, and Simulation) via the FDE model.

The base salary range for this full-time position is $255,000 -$351,000 annually in addition to bonus, equity and benefits.

The base salary range for this full-time position is $255,000 -$351,000 annually in addition to bonus, equity and benefits.
Technical Roadmap & Vision: Keep a strong pulse on breakthrough trends in AGI and systems engineering.
Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

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.

This listing is sourced directly from DiDi Labs's careers page and normalized into a canonical job model.