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GPU Kernel Generator Developer
2 months ago
We are committed to building great products that accelerate next-generation computing experiences. Our mission is to push the limits of innovation to solve the world's most important challenges.
The RoleYou will develop a high-performance GPU kernel generator to deliver machine learning tensor operations with support for layer fusion. This role requires collaboration with teams involved with all aspects of the machine learning and math libraries.
The PersonWe are looking for a talented library developer who is open to continuously learning and is excited about innovative solutions. A great candidate will be a strong collaborator who can analyze the performance of GPU kernels and provide insight on optimization paths.
Key Responsibilities- Contribute to the design and implementation of AMD's GPU kernel generator used in a variety of high-performance machine learning libraries and frameworks.
- Analyze the performance of GPU kernels and provide insight on optimization paths.
- Develop optimization and analysis passes on graph representations of GPU kernels.
- Communicate and collaborate with key technical experts across AMD and with our partners and customers to improve ROCm applications, libraries, and tools, as well as hardware.
- Deliver high-quality code and documentation following best practices for open-source software development.
- Apply software engineering methodologies to ensure robust, maintainable code.
- Develop technical relationships with peers and partners.
- Hands-on professional experience writing and optimizing GPU code.
- Strong background developing applications and libraries in modern C++.
- Understanding of compiler technology fundamentals such as abstract syntax trees, control flow graphs, data flow analysis, IR, and target lowering.
- Experience with best practices in software development, including testing, profiling, debugging, documentation, version control, and issue tracking.
- Experience with low-level optimization techniques; assembly programming and/or vectorization.
- Bachelor's or Master's degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
