Riel St. Amand is a Machine Learning Engineer and Full-Stack Developer with 5+ years of experience deploying production AI systems at scale. Currently building invoice automation pipelines at IPN Retail, Riel has achieved remarkable results including 100% accuracy on over 1 million COVID-19 diagnoses through ensemble neural networks and 95% processing time reductions in document automation workflows.
Riel’s journey into software began during his final semester studying Biology at the University of Dayton, where he taught himself programming and quickly transitioned into professional development. His unique background spans healthcare AI, enterprise chatbots, and large-scale web applications serving millions of users. He has worked with Fortune 500 companies including Nationwide, Bridgestone, and CareSource, building systems that handle everything from real-time medical diagnostics to tire manufacturing tracking.
As a conference speaker, Riel is passionate about making machine learning accessible to developers. His hands-on workshop at Kansas City Developer Conference 2022 taught 50+ developers practical ML implementation, and he regularly shares his expertise in deploying AI systems that solve real-world business problems.
When not building neural networks or optimizing React applications, Riel enjoys exploring the intersection of traditional ML techniques with modern AI approaches, always focused on production-ready solutions that deliver measurable impact.