Summary
Sangwu Lee is a machine learning engineer with a decade of experience building and deploying ML systems across research labs and startups, currently creating generative visual models at krea.ai. He has driven multimodal LLM/VLM research at Carnegie Mellon, delivering SOTA results, authoring conference papers, and developing a parameter- and cost-efficient VLM architecture. At the University of Rochester he moved projects from research to production—training hundreds of thousands of models on HPC, launching dataset collection platforms, and shipping ML endpoints for medical AI. As a founding engineer at Oleve he combined ML research, full-stack development, and product delivery, and he brings practical DevOps and infra experience (FastAPI, Docker, Replicate) alongside model fine-tuning at scale. Notably, Sangwu’s work emphasizes keeping inference costs low while preserving performance, reflecting a pragmatic focus on production-ready, resource-efficient ML.
9 years of coding experience
8 years of employment as a software developer
Bachelor of Science - BS, Mathematics and Computer Science, Freshmen, Bachelor of Science - BS, Mathematics and Computer Science, Freshmen at University of Rochester
Computer Science, Computer Science at UWC-USA
English, Japanese, Korean, Spanish