Summary
Nima Harzevili is an AI Engineer with 9 years of experience building production-grade ML and GenAI systems, currently developing RAG-enabled medical document pipelines and deploying LLM services at HGS. He blends deep research insight from a PhD track and security-focused work on TensorFlow/PyTorch vulnerabilities with hands-on MLOps—containerized CI/CD, Amazon ECS/ECR, S3, MongoDB, and hybrid cloud/on-prem LLM inference stacks. Nima has led tool-building and fuzzing research that uncovered dozens of DL vulnerabilities and prototyped LLM-based repair tools, demonstrating a rare mix of vulnerability research and practical AI engineering. Equally comfortable designing prompt engineering and vector-search solutions as he is optimizing deployment workflows, he collaborates closely with clinicians to translate clinical requirements into reliable GenAI features. Outside work, he maintains a public GitHub and scholarly presence, signaling both applied delivery and academic rigor.
9 years of coding experience
10 years of employment as a software developer
Bachelor's degree, Computer Software Engineering, 17.84, Bachelor's degree, Computer Software Engineering, 17.84 at University of Applied Science and Technology
Master's degree, Computer Software Engineering, 17.17, Master's degree, Computer Software Engineering, 17.17 at Qazvin Islamic Azad University
Doctor of Philosophy - PhD, Electrical Engineering and Computer Science, Doctor of Philosophy - PhD, Electrical Engineering and Computer Science at York University
Associate's degree, Computer Software Engineering, 16.46, Associate's degree, Computer Software Engineering, 16.46 at Shahid Rajaei Technical University
English, Turkish, Persian