Summary
Damien Benveniste is a Staff ML Engineer with over a decade of experience building production-grade machine learning systems and driving measurable business impact. He has led ML efforts across startups and hyperscale companies—most notably generating ~$40M in annualized revenue impact at Meta and architecting an AI product that enabled a $44M acquisition at Medallia. As a founder he scaled The AiEdge into a profitable ML education platform reaching 130K subscribers and 4,300 students worldwide, and he runs consulting practice Intelligent Engineering Systems to help organizations operationalize ML. His technical focus spans LLMs, RAG pipelines, fine-tuning, distributed training and inference optimization, complemented by hands-on leadership in model automation and deployment. Trained as a physicist with a PhD from Johns Hopkins and advanced ML study at Georgia Tech, he blends rigorous research instincts with product-minded engineering. Based in Long Beach, CA, Damien combines academic depth, startup grit, and enterprise impact to lead high-stakes ML programs end-to-end.
10 years of coding experience
15 years of employment as a software developer
Johns Hopkins University
Master's Degree, Computer Science, Machine learning, Master's Degree, Computer Science, Machine learning at Georgia Institute of Technology
Bachelor's degree, Physics, Bachelor's degree, Physics at Université Pierre et Marie Curie (Paris VI)
Master's degree, Condensed Matter and Materials Physics, Master's degree, Condensed Matter and Materials Physics at École Normale Supérieure Paris-Saclay
English, French, Spanish