Summary
Hussain Kadhem is a Senior Machine Learning Compiler Engineer with 11 years of experience blending compiler development, high-performance computing, and scientific machine learning to deploy deep learning and vision pipelines on accelerator hardware. His work crosses domains—from implementing Fortran parallel features in LLVM and optimizing compilers at IBM and Intel to enabling autonomous-driving ML stacks using TorchDynamo, ONNX, MLIR, and TensorRT at General Motors. Trained as a mathematician (PhD candidate at UC Berkeley; MA Cambridge) and experienced in quantum many-body simulation and AFQMC, he brings rigor in numerical linear algebra and Monte Carlo methods to practical compiler and systems problems. He thrives in large-scale, interdisciplinary co-design environments and has a track record of contributing to open-source compiler ecosystems and exascale projects. Completely blind from birth and accompanied by a guide dog, he is also a committed advocate for accessibility and diverse representation in STEM.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Applied Mathematics, Doctor of Philosophy - PhD Applied Mathematics at University of California, Berkeley
Bachelor of Science - BS Mathematics, Bachelor of Science - BS Mathematics at University of Toronto
High School Diploma, High School Diploma at Don Mills Collegiate Institute
Master's degree Mathematics, Master's degree Mathematics at University of Cambridge
exchange program mathematical physics, exchange program mathematical physics at University of Edinburgh
English, Arabic