Summary
Nick Halmagyi is an AI engineer and former theoretical physicist who blends 15 years of academic research with nine years of industrial machine learning experience to deliver production-grade AI systems across finance, healthcare, cybersecurity, logistics and more. He has led small-to-medium teams and driven technical strategy at organizations from startups to global enterprises, recently holding principal roles at Karh and Trio Workforce Solutions. His background includes a CNRS research professorship and a Fermi‑McCormick fellowship, reflecting deep expertise in mathematical modeling that he translates into novel ML solutions like large-graph recommendation systems. Comfortable in both research and engineering contexts, he builds end-to-end pipelines, REST APIs, and cloud-native deployments while advising enterprises on ML capability and transformation. Based in Somerville, MA, he pairs an academic instinct for elegant, provable methods with pragmatic delivery—outside work he balances physics and code with bluegrass and surfing.
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Theoretical and Mathematical Physics, Doctor of Philosophy (Ph.D.), Theoretical and Mathematical Physics at University of Southern California
Bachelor’s Degree, Theoretical and Mathematical Physics, Bachelor’s Degree, Theoretical and Mathematical Physics at University of Adelaide
The University of Sydney
English, French