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← DiDi Labs

Senior/Sr. Staff AI Infrastructure Engineer, Inference & Optimization

DiDi Labs
Location
San Jose, CA
Posted
9 days ago
Department
Artificial Intelligence
Salary
$169,783 - $351,000
What they actually want (must-haves)
  • Master’s or higher degree in Computer Science, Software Engineering, Systems Engineering, or a closely related technical field
  • 3-8+ years of industry experience in high-performance computing, AI infrastructure, model optimization, or embedded deployment
  • Strong proficiency in C++ and Python
  • Solid expertise in parallel programming (CUDA, OpenMP) and low-level system profiling tools
  • Deep familiarity with mainstream inference engines (e.g., TensorRT, ONNX Runtime)
  • Practical understanding of modern GPU hardware architectures (e.g., NVIDIA Hopper, Thor)
Nice to have
  • Hands-on experience optimizing and deploying AI models on the NVIDIA Thor platform
  • Proven track record of serving large foundation models (e.g., LLaMA, Qwen, GPT) in production
  • Background in deep learning training frameworks (PyTorch)
  • Experience deploying real-time, high-availability AI workloads in autonomous vehicles, robotics, or edge devices
What the job really is

The Senior/Sr. Staff AI Infrastructure Engineer will focus on optimizing and deploying AI models for autonomous vehicles, ensuring high efficiency and low latency. Responsibilities include designing inference pipelines, conducting system stability initiatives, and collaborating with various teams to enhance model performance and reliability.

Benefits
  • Base salary range of $169,783 - $351,000 annually
  • Bonus
  • Equity
  • Benefits
Things to weigh
  • Salary range is quite broad, which may indicate variability based on experience and negotiation
  • Focus on cutting-edge AI technology may require continuous learning and adaptation
  • Role involves significant technical leadership and cross-functional collaboration, which may be demanding
Job score4.4/5
Benefits2/5
Freshness5/5
Career value5/5
Role clarity5/5
Pay transparency5/5

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