AI Computing Software Development Engineer, Tensorrt

NVIDIA NVIDIA · Semiconductors · Shanghai, China

NVIDIA is seeking an AI Computing Software Development Engineer for its TensorRT team to craft and develop robust, scalable inferencing software for GPUs. The role involves performance analysis, optimization, tuning, and collaborating with various teams to guide the direction of machine learning inferencing. Requires a Masters or higher degree, 2+ years of software development experience, strong C/C++ skills, and familiarity with deep learning frameworks.

What you'd actually do

  1. Craft and develop robust inferencing software that can be scaled to multiple platforms for functionality and performance
  2. Performance analysis, optimization and tuning
  3. Closely follow academic developments in the field of artificial intelligence and feature update TensorRT
  4. Provide feedback into the architecture and hardware design and development
  5. Collaborate across the company to guide the direction of machine learning inferencing, working with software, research and product teams

Skills

Required

  • C/C++ programming
  • software design
  • debugging
  • performance analysis
  • test design
  • deep learning frameworks (TensorFlow, PyTorch)
  • software development experience

Nice to have

  • Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related computing focused degree
  • curiosity about artificial intelligence
  • awareness of the latest developments in deep learning like LLMs, generative and recommender models

What the JD emphasized

  • ability to work on a fast-paced delivery-focused team is required
  • excellent interpersonal skills are a must
  • Masters or higher degree
  • 2+ years of relevant software development experience
  • Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design
  • Proactive and able to work without supervision
  • Excellent written and oral communication skills in English

Other signals

  • building the inferencing software
  • performance analysis, optimization and tuning
  • guide the direction of machine learning inferencing