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Senior AI Video Architecture Engineer

NVIDIA Corporation

China, ShanghaiFirmwareSoC / ASICPosted Nov 7, 2026
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Skills named in this posting

  • C
  • C++
  • Python
  • CUDA
  • PyTorch / TensorFlow
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.

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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