GPU Computing Engineer
We are now looking for an CPU computing engineer based in Shanghai.
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 becomes more and more important in AI-City and self-driving car. 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 and TensorRT, etc.
What you’ll be doing:
Analysis the cuDNN and TensorRT stability and performance issues from customer or internal team
Work with internationally distributed team with remote locations in US, APAC and India for cuDNN and TensorRT developing.
Extract the feature requirement or FAQ from the analysis and development and generate the documents
What we need to see:
Bachelor of Computer Science or Electrical Engineering is required and Master Degree is preferred.
3+ years of related work
Strong programming skills in C and C++ and/or python
Have knowledge about the popular inference network and layers
Experience working with deep learning frameworks like Caffe, TensorFlow or Torch
Strong written and verbal communications 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