Summary
Zimin Park is a Machine Learning Engineer based in Seoul with 8 years of experience building production-grade ML systems focused on information retrieval, recommendation, and retrieval-augmented generation. He has shipped RecSys and RAG-driven services across commerce, OTT, and financial domains—work that includes maintaining a 2M-subscriber chatbot, CI/CD and continuous training pipelines with Metaflow and Kubernetes, and AWS infra via CDK. At Upstage he drove QA and table-understanding for PDFs, automated insurance coverage determination, and delivered quiz-generation and bank exam QA systems, while earlier roles emphasized sequential recommendation and A/B-driven targeting. He contributes to open-source PyTorch tooling—improving data loaders, validation flows, and tensorboardX integration—and brings hands-on OCR research experience from GitHub projects. With a math background from POSTECH, he combines rigorous quantitative thinking with practical deployment experience, often bridging research prototypes to scalable production services.
9 years of coding experience
5 years of employment as a software developer
학사 수학, 학사 수학 at Pohang University of Science and Technology