This repository compiles interview questions and study notes for NLP algorithm engineers, covering topics across named entity recognition, probabilistic graphical models (HMM, MEMM), sequence labeling, and transformer-based models. It serves as a preparation resource for job candidates in the NLP field, organizing answers and explanations across multiple NLP subdomains.