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THE ROLE:
You will develop a high-performance GPU kernel generator to deliver the machine learning tensor operations with support for layer fusion. AMD is searching for talented and motivated computer scientists and compiler engineers to implement machine learning primitives as part of the AMD Radeon Open Ecosystem (ROCm). In this role, you will be collaborating with teams involved with all aspects of the machine learning and math libraries.
THE PERSON:
We are looking for a talented library developer who is looking to make an impact on deep learning performance. A great candidate will be a strong leader who is open to continuously learning and is excited about innovative solutions.
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.
PREFERRED EXPERIENCE:
- Hands-on professional experience writing and optimizing GPU code.
- Strong background developing applications and libraries in modern C++ and Python.
- 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.
- Understanding of graph theory.
ACADEMIC CREDENTIALS:
- Master's degree or PhD in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, or equivalent.