Corbin Mcelhanney is a seasoned software engineer with a decade of experience building high-performance systems across cloud, database, and quantum-computing domains. Currently at Snowflake, he focuses on algorithms and performance profiling for core database operators, after integrating QuEra’s quantum processor with AWS Braket and contributing numerical optimization tooling in Julia. He has a track record of shipping production software—from event-driven Kotlin services and Pulsar architectures to distributed deep-learning runners on GCP—and brings strong full-stack instincts formed at startups and large firms like Microsoft and AMD. Corbin pairs rigorous academic training (University of Waterloo; MS at Stanford) with hands-on systems craft, and he’s known for translating research-grade ideas into robust, scalable engineering solutions. An often-overlooked strength is his history leading cross-functional remote teams and automating developer workflows, which accelerates delivery in complex, novel domains.
10 years of coding experience
4 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Stanford University
Webber Academy Diploma College/University Preparatory and Advanced High School/Secondary Diploma Program, Webber Academy Diploma College/University Preparatory and Advanced High School/Secondary Diploma Program at Webber Academy
Bachelor of Software Engineering (BSE) Computer Software Engineering, Bachelor of Software Engineering (BSE) Computer Software Engineering at University of Waterloo
Contributions:12 commits, 6 pushes, 2 branches in 1 day
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Corbin Mcelhanney - Software Engineer at Snowflake