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We are seeking an experienced software engineer to join our team, which maintains the CUDA C++ Core Libraries (Thrust, CUB, libcudacxx). These libraries provide the fundamental abstractions and parallel algorithms that make CUDA more delightful for a wide range of computational workloads, including deep learning, scientific computation, data science, self-driving cars, video games, and virtual reality. As we explore exposing this functionality to other languages like Python, you will play a crucial role in shaping the future direction of CUDA and accelerating general-purpose computation on the GPU.
What You'll Be Doing:
Design and implement efficient CUDA C++ algorithms, tackling challenges ranging from API design to performance optimization
Evangelize, architect, and implement new features to extend the reach of our libraries beyond C++ to Python and other languages.
Collaborate across teams to drive development efforts and integrate our libraries into diverse ecosystems.
Write effective, maintainable, and well-tested code that adheres to our high standards of quality.
Contribute to the open-source community and engage with users to gather feedback and improve our libraries.
What We Need to See:
BS or MS degree in Computer Science, Electrical Engineering, or a related field or equivalent experience.
Strong programming skills in C++ and experience with Python or other programming languages.
5+ years of related development experience.
Experience with C++ templates, parallel programming, and working with large codebases.
Experience contributing to open-source software components.
Excellent written communication and presentation skills.
Ways to Stand Out from the Crowd:
Prior experience with parallel computing and GPU architectures.
Experience with CUDA C++ libraries such as Thrust, CUB, stdexec, and libcudacxx.
Involvement in ISO C++ Standard Committees/Working groups.
Leadership experience in managing open-source software components.
You will also be eligible for equity and .
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