Nvidia-posted 2 months ago
$184,000 - $356,500/Yr
Senior
Hybrid • Santa Clara, CA
5,001-10,000 employees
Computer and Electronic Product Manufacturing

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join our team and see how you can make a lasting impact on the world! NVIDIA is seeking a passionate and experienced engineer for our video IP team to develop innovative AI algorithms in the field of video compression/processing. You will work on DL/ML based algorithms and next generation of encoder and decoder HW algorithm/architecture. If you are passionate about the latest deep learning and video compression research and motivated to prototype ground up algorithms with a keen focus on delivering impactful solutions, then this role will be a great fit for you!

  • Research and development into deep learning networks for video compression, video pre/post processing.
  • Video codec algorithm / HW architecture development
  • Modeling of multimedia hardware.
  • Master's degree or PhD in Electrical Engineering, Computer Science, or equivalent experience.
  • At least 6+ years industry experience in deep learning and/or video compression field.
  • Hands on experience with PyTorch / Tensorflow is must have.
  • Hands on experience with video codecs such as H264 (AVC)/H.265 (HEVC)/AV1 is must have.
  • Excellent C/C++ and Python programming skills.
  • Good communication skills.
  • Prior experience with the successful delivery of AI features in products.
  • Research/development experience into video compression standards (H.264/HEVC/AV1).
  • Experience with GPU optimization frameworks, Tensor RT or cuDNN.
  • Equity and benefits.
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