Description
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, AV2 or VVC. Experience with coding agents, such as Cursor, Codex, and Claude code. Background with computer vision projects such as optical flow, stereo, super-resolution, frame rate up-conversion, etc. Experience with CUDA.