Matt Smith is a software engineer with 11 years of experience, currently building multimodal LLMs as a Machine Learning Engineer at Meta. He brings deep ML and production engineering experience from multiple roles at Yelp, where he shipped NLP, computer vision, and user behavior models and improved search ranking and data-quality tooling. A Waterloo BMath dual major in CS and Combinatorics & Optimization, he pairs strong theoretical foundations with practical systems work—evident from contributions to deployment tooling like dh-virtualenv packaging improvements. Comfortable across the stack, he focuses on reliability, maintainability, and diagnostics for large-scale ML systems. Based in Old Toronto, he blends research-oriented modeling with hands-on engineering that moves models into production.
11 years of coding experience
5 years of employment as a software developer
Bachelor of Mathematics - BMath, Dual major in Honours Computer Science and Honours Combinatorics & Optimization, With Distinction - Dean's Honours List, Bachelor of Mathematics - BMath, Dual major in Honours Computer Science and Honours Combinatorics & Optimization, With Distinction - Dean's Honours List at University of Waterloo
Contributions:5 commits, 1 PR, 2 comments in 1 day
Contributions summary:Matt focused on improving the reliability and maintainability of the virtualenv package. Their contributions included updating shebang handling, fixing line lengths, and addressing issues introduced by those fixes. These changes primarily involved modifying Python scripts and test files within the `dh_virtualenv` package, demonstrating a focus on deployment and packaging aspects.
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