This repository compiles common interview questions and answers for large language model algorithm positions. It covers foundational topics including linear algebra, calculus, and probability, as well as model architectures such as Transformers, attention mechanisms, Mixture of Experts, and diffusion models. Additional topics include retrieval-augmented generation, parameter-efficient fine-tuning, model quantization, and knowledge distillation.