AI Computing Development Engineer, Tensorrt and Tensorrt-llm

NVIDIA NVIDIA · Semiconductors · Shanghai, China

NVIDIA is seeking software engineers to develop and optimize AI inference software (TensorRT/TensorRT-LLM) for GPUs. The role involves performance analysis, tuning, integrating new advancements, and collaborating across teams to shape the future of machine learning inferencing.

What you'd actually do

  1. Design and develop robust inferencing software (TensorRT/TensorRT-LLM) optimized for functionality and performance across platforms
  2. Perform performance analysis, optimization, and tuning of deep learning inference workloads
  3. Track and integrate academic and industry advancements in AI and feature-update TensorRT/TensorRT-LLM accordingly
  4. Provide feedback into architecture and hardware design and development
  5. Collaborate across hardware, software, and research teams to shape the direction of machine learning inferencing across NVIDIA platforms

Skills

Required

  • C/C++ or Python programming
  • Software design
  • Debugging
  • Performance profiling
  • Test design
  • Deep learning frameworks (PyTorch, TensorRT/TensorRT-LLM, NeMo, vLLM)
  • AI and deep learning concepts (generative models, multimodal systems, large neural networks)
  • Software engineering best practices

Nice to have

  • Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics, or related computing-focused field (or equivalent experience)
  • Experience with TensorRT/TensorRT-LLM
  • Experience with vLLM
  • Experience with NeMo
  • Academic and industry advancements tracking
  • Architecture and hardware design feedback
  • Cross-functional collaboration

What the JD emphasized

  • delivery-focused environment is required
  • excellent interpersonal skills are a must
  • Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics, or related computing-focused field (or equivalent experience)
  • Strong C/C++ or Python programming and software design experience, including debugging, performance profiling, and test design
  • 2+ years working experience
  • Strong curiosity about artificial intelligence and familiarity with the latest developments in deep learning — including generative models, multimodal systems, and large neural networks
  • Experience working with deep learning frameworks such as PyTorch, TensorRT/TensorRT-LLM, NeMo, or vLLM
  • Proactive, self-driven, and able to work independently
  • Excellent written and verbal communication skills in English
  • Demonstrated ability, commensurate with experience, to take technical ownership, solve complex problems, and contribute effectively in cross-functional environments

Other signals

  • inference software development
  • performance optimization
  • deep learning frameworks