Umang Yadav is a Staff Software Engineer at AMD with eight years of experience building ML acceleration stacks, currently driving MLIR-based kernel generation work on rocMLIR and contributing to the ROCm ecosystem. He has deep compiler and graph-compiler expertise from leading roles on MIGraphX, UIF, and TVM-based toolchains, and earned an AMD spotlight award for his FP8 work. Prior experience includes building Relay/TVM graph transformers and high-performance kernels for ASICs at Untether AI and TVM-based compiler contributions at Huawei, showing a consistent focus on turning research-grade compiler ideas into production-ready inference tooling. Based in Old Toronto, he is an active open-source contributor with a public GitHub profile centered on ML acceleration projects, combining strong systems-level engineering with hands-on kernel and codegen optimization experience.
8 years of coding experience
8 years of employment as a software developer
High School Certificate Physics Chemistry Maths, High School Certificate Physics Chemistry Maths at Smt. V. D. Desai Wadiwala (Bhulka Bhavan) High School
Bachelor of Technology (B.Tech.) Electronics and Communications Engineering, Bachelor of Technology (B.Tech.) Electronics and Communications Engineering at National Institute of Technology Surat
Master of Applied Science (MASc) Electrical and Computer Engineering, Master of Applied Science (MASc) Electrical and Computer Engineering at University of Toronto
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