Michael Yang is a highly accomplished AI/ML practice leader with a distinguished track record in leading the successful delivery of AI/ML projects. He has been instrumental in collaborating with startups to medium-sized companies to implement cutting-edge AI/ML solutions, consistently ensuring client satisfaction and project success. Michael's expertise extends to serving as the primary Machine Learning Architect, contributing to the design and execution of AI/ML projects, covering diverse areas such as forecasting, NLP, recommender system, computer vision, MLOps, and generative AI. His proficiency in applying AWS's ML well-architected framework pillars has resulted in the development of robust and scalable end-to-end AI/ML systems across various stages of the ML lifecycle.

With a solid background in ML services and generative AI, Michael has demonstrated exceptional skills in implementing generative AI applications, including medical SOAP notes generators, domain specific chatbots, and image generator applications. He is experienced with Large Language Model (LLM), Stable Diffusion models, foundational model fine-tuning, retrieval augmented generation (RAG), model quantization, and MLOps. Beyond technical prowess, Michael has successfully managed and mentored ML and data engineers, facilitating the transition of engineers into solution architects in their respective domains, highlighting his commitment to talent development and professional growth.