Paul Iusztin is a senior ML and MLOps engineer with over seven years of experience building GenAI, computer vision, and MLOps solutions across industries. His most recent industry contribution was at Metaphysic, where he served as one of the core engineers taking large neural networks to production, work that demanded both deep learning expertise and serious systems engineering. Earlier in his career he built applied ML systems at CoreAI, Everseen, and Continental.

Paul is equally known for his educational work. He is the founder of Decoding ML, an educational channel on production-grade machine learning that publishes posts, articles, and open source courses to help engineers build real-world ML and AI systems beyond the proof-of-concept stage. He is the author of the bestselling LLM Engineer’s Handbook, co-written with Maxime Labonne, a book that walks readers through the full lifecycle of an LLM-powered system, from data and training to evaluation and deployment. He also leads an Agentic AI Engineering course and writes for the Decoding AI magazine, teaching AI engineering end to end, from data gathering to deployment.