Summary
Reza Barzegar is a Senior MLOps Developer with eight years of experience bridging AI research and production systems, currently driving agentic AI and LLM engineering in clinical simulation and enterprise settings. With a Master’s in Computer Science and a research background in curriculum learning and neural team recommendation, he has published work that improved training efficiency and model accuracy while deploying scalable pipelines for large datasets. Reza has hands-on expertise across the full ML lifecycle—fine-tuning PyTorch models, designing data pipelines, and operationalizing models in clinical and corporate environments. Notably, he led development of an agentic clinical interview simulator using LangGraph and OpenAI models, demonstrating a knack for turning cutting-edge research into human-centered tools. He balances rigorous experimentation with pragmatic deployment, and is especially interested in agentic architectures and adaptive learning systems that make AI more interactive and trustworthy.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Computer Engineering, Bachelor of Science - BS, Computer Engineering at Ferdowsi University of Mashhad
Master's degree, Computer Science, Master's degree, Computer Science at University of Windsor