GPU Computing Engineer Intern (Start ASAP)

NVIDIA has continuously reinvented itself over two decades.

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.

This is our life’s work — to amplify human imagination and intelligence. AI is becoming more and more important in AI-City and self-driving cars. NVIDIA is at the forefront of the AI-City and self-driving revolution and providing powerful solutions for them. All these solutions are based on GPU-accelerated libraries, such as CUDA, cuDNN TensorRT, etc. Now, we are now looking for a CPU computing engineer intern based in Shanghai.

What you’ll be doing

• Analysis of the cuDNN and TensorRT stability and performance issues from a customer or internal team
• Work with an internationally distributed team with remote locations in the US, APAC, and India for cuDNN and TensorRT development.
• Extract the feature requirement or FAQ from the analysis and development and generate the documents.

What we need to see

• A Bachelor of Computer Science or Electrical Engineering is required and a Master's Degree is preferred.
• Strong programming skills in C and C++ and/or Python
• Know the popular inference network and layers
• Experience working with deep learning frameworks like Caffe, TensorFlow, or Torch
• Strong written and verbal communication in both English and Mandarin
• Ability to work well in a diverse team environment as well as with cross-site peers
• Strong customer communication skills, powerfully motivated to provide highly responsive support as needed