Nvidia is hiring a
Deep Learning Architecture Engineer, Video

NVIDIA video team is located in Shanghai, focuses on algorithm, architecture and HW design of video/CV solutions in all NVIDIA products, including datacenter, desktop, automotive, embedded system, etc. More than 80% of global internet traffic is video stream and it’s still growing, there’s a strong demand for reducing video bandwidth and increasing video quality. We are looking for architecture engineers to address this problem in a DL based approach.

What you’ll be doing:

• Develop DL based solutions for video pre/post-processing, compression, etc. Including algorithm study, implementation, performance tuning, and productization.

• Study new video compression/computer vision technology, specifications, papers, etc.

• Define the chip architecture of NVIDIA's next-generation video/CV solution, collaborate with ASIC team to deliver HW design.

What we need to see:

• Master Degree or above in Compute Science or Electronic Engineering

• Minimum of 2+ years’ experience in deep learning or video codec projects.

• Experience with deep learning training frameworks such as Tensorflow, Pytorch, Caffe.

• Good programming skill and C/C++ or python coding abilities.

• Fluent English and good communication skill.

Ways to stand out from the crowd:

• Project experiences on deep learning-based video pre/post processing, compression.

• Experience with video codec such as H264/AVC, HEVC, VP9, AV1 or VVC

• Background with computer vision projects such as optical flow, stereo, super-resolution, frame rate up-conversion, etc.

• Experience with CUDA.