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What You'll Be Doing
As a member of our team, you will use your design abilities, coding expertise, creativity, and community engagement to develop and enhance the functionality and performance of NVIDIA GPUs such that the current and future generations of Python users can enjoy the programmability and take full advantage of the NVIDIA CUDA platform, including both NVIDIA hardware and software. Specifically, you will be working to:
Architect, prioritize, and develop new features in CUDA Python
Analyze, identify, and improve the UX and performance of CUDA software in Python
Write effective, maintainable, and well-tested code for production use
Bridge the language gap between existing CUDA C/C++ solutions and Python
Understand and address unique challenges in developing and deploying Python GPU solutions
Identify key open source players in the Python/PyData ecosystem, and engage with them to develop and drive necessary protocols and standards for the NVIDIA CUDA platform
Evangelize CUDA programming in Python to encourage and empower adoption of the NVIDIA CUDA platform
What We Need To See
BS, MS or PhD degree in Computer Science, Electrical Engineering or related field (or equivalent experience)
5+ years of relevant industry experience or equivalent academic experience after BS
Strong Python programming and deployment skills with track record of driving formulation and/or adoption of Python community standards
Fluent C/C++ and CUDA programming skills
Background in AI, high performance computing or performance critical applications
Track record ofdeveloping/maintainingPython projects, and/or engaging with Python users on UX or performance improvements
Experience in designing, developing, tuning, navigating, and/or maintaining a large, complex, multi-language software stack (between C/C++/CUDA and Python)
Good written communication, collaboration, and presentation skills with ability of operating across team boundaries
Experience in distributed programming in C/C++/Python using MPI, Dask, Legate, or other distributed programming models/frameworks
Knowledge of generating Python bindings for mid- to large- size C/C++ codebases
Ways To Stand Out From The Crowd
Deep understanding in the CUDA programming model and language features
Familiarity with Python ecosystem, language idioms, and pioneering solutions
Dexterity with compilers, static/dynamic analysis techniques, and/or dynamic codegeneration/transpilation/compilation
Experience in using or developing the LLVM/Clang compiler infrastructure
Experience in memory management of a multi-language project or development of domain specific libraries/languages for AI, Data Analytics or Scientific Computing
You will also be eligible for equity and .
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