英伟达GPU Driver Profiler Engineer
任职要求
• B.S. EE/CS or equivalent experience with 2+ years of experience or M.S. with 1+ years' experience, or Ph.D. • Strong programming ability in C, C++, and scripting languages. • Quick learner, willing to dive in where needed and debug complex code and UMD/KMD interactions • Driver experience (preferably kernel driver…
工作职责
• Revising/updating/testing kernel interfaces and reviewing code used by the Developer Tools team • Collect requirements from software developer tools' features and work with the kernel team to co-design new interfaces • Implementation of new features as well as HAL to support new GPU architectures • Support various OS's and driver architectures: Windows WDDM, Linux Desktop, Mobile Linux and QNX. • Contribute to next-gen architectures (both SW and HW)
THE ROLE: Triton is a language and compiler for writing highly efficient custom deep learning primitives. It's widely adopted in open AI software stack projects like PyTorch, vLLM, SGLang, and many others. AMD GPU is an official backend in Triton and we are fully committed to it. If you are interested in making GPUs running fast via developing the Triton compiler and kernels, please come join us!
THE ROLE: As a core member of the team, you will play a pivotal role in optimizing and developing deep learning frameworks for AMD GPUs. Your experience will be critical in enhancing GPU kernels, deep learning models, and training/inference performance across multi-GPU and multi-node systems. You will engage with both internal GPU library teams and open-source maintainers to ensure seamless integration of optimizations, utilizing cutting-edge compiler technologies and advanced engineering principles to drive continuous improvement.
THE ROLE: As a core member of the team, you will play a pivotal role in optimizing and developing deep learning frameworks for AMD GPUs. Your experience will be critical in enhancing GPU kernels, deep learning models, and training/inference performance across multi-GPU and multi-node systems. You will engage with both internal GPU library teams and open-source maintainers to ensure seamless integration of optimizations, utilizing cutting-edge compiler technologies and advanced engineering principles to drive continuous improvement.