Nathan St Pierre is a Machine Learning Screencast SME and AI practitioner with 10 years of experience building production-ready ML systems and educational technology that scale. He blends PhD-level research methods in education with hands-on engineering—designing custom neural nets, RAG architectures, vector embeddings, and adaptive learning platforms using PyTorch/TensorFlow. His work has halved data processing time, boosted learner engagement by over a third, and produced an industry-facing RAG content assistant and adaptive quiz system with real-time analytics. An experienced educator and researcher, he has published widely, taught at university level, and translated pedagogical insights into measurable product improvements. Based in Palm Bay, FL, he pairs deep domain expertise in learning analytics with practical API and pipeline implementation, and even lists a compiler interest on GitHub hinting at a broader systems-level curiosity.
10 years of coding experience
Bachelor of Music Vocal Music Education, Bachelor of Music Vocal Music Education at University of Hartford
Master of Education - MEd Kodály Music Education, Master of Education - MEd Kodály Music Education at Loyola University Maryland
Doctor of Philosophy - PhD Music Teacher Education, Doctor of Philosophy - PhD Music Teacher Education at George Mason University
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