Richard North is a Machine Learning Engineer with 10 years of experience applying parallel computing and software optimization to production-grade systems, currently rotating in Intel’s ML organization while pursuing an M.S. in Artificial Intelligence at UT Austin. He has a track record of delivering dramatic performance improvements—up to 30x speedups—by optimizing CPU/GPU algorithms and kernel implementations and contributing to OneDAL and scikit-learn-intelex. Comfortable in both Python and C++, he blends classical ML expertise with low-level performance tuning and hands-on open-source development, including expanding test coverage and public CI. He has driven measurable business impact through performance tools that helped capture market share and enabled faster onboarding via automation. Beyond engineering, he has led large employee resource initiatives and partnered with nonprofits to broaden the STEM pipeline, demonstrating commitment to mentorship and inclusion. Colleagues rely on him to bridge research-quality experimentation and production-ready, standards-conformant ML libraries.
10 years of coding experience
Master of Science - MS, Artificial Intelligence, Master of Science - MS, Artificial Intelligence at The University of Texas at Austin
Bachelor of Science (B.S.), Computer Science and Mathematics, Bachelor of Science (B.S.), Computer Science and Mathematics at Texas Southern University
Sandia OpenSHMEM is an implementation of the OpenSHMEM specification over multiple Networking APIs, including Portals 4 and the Open Fabric Interface (OFI). Please click on the Wiki tab for help with building and using SOS.
Contributions:27 pushes, 6 branches, 1 comment in 2 years 2 months
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Richard North - Machine Learning Engineer Rotation