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What you'll be doing:
As a member of our team, you will use your design abilities, coding expertise, and creativity to deliver a GPU-accelerated library used in NVIDIA products ranging from Data Center, Automotive and Embedded systems.
Architect and implement new features to deliver an amazing user experience for our internal customers, like cuDNN, cuBLAS, and TensorRT
Design and develop validation methodologies so that our library is robust across a diverse cross product of hardware, OSes, and platforms, including simulators and emulators for future GPUs
Write effective, maintainable, and well-tested code
What we need to see:
MS or PhD degree in Computer Science, Electrical Engineering or related field (or equivalent experience)
Deep C++ programming and problem-solving skills, including debugging, performance analysis, documentation, and test design
6+ years of relevant software development experience
Background in working with large codebases
The ability to work independently, define project goals and scope, and lead your own development effort
Strong written communication as well as presentation skills
Ways to stand out from the crowd:
Prior experience with parallel computing
Understanding of Deep Learning and AI
Fluency in build systems (e.g. Make, CMake, and/or Bazel)
Multiple contributions to open source software
You will also be eligible for equity and .
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