LLM Interview Preparation LLM Tools

Repositories containing interview questions, answers, and study guides specifically for LLM/AI engineer and ML roles. Does NOT include general career advice, resume tools, or job application automation platforms.

There are 25 llm interview preparation tools tracked. 3 score above 50 (established tier). The highest-rated is KalyanKS-NLP/LLM-Interview-Questions-and-Answers-Hub at 56/100 with 809 stars.

Get all 25 projects as JSON

curl "https://pt-edge.onrender.com/api/v1/datasets/quality?domain=llm-tools&subcategory=llm-interview-preparation&limit=20"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

#	Tool	Score	Tier	Stars	Language
1	KalyanKS-NLP/LLM-Interview-Questions-and-Answers-Hub 100+ LLM interview questions with answers.	56	Established	809	—
2	datawhalechina/daily-interview Datawhale成员整理的面经，内容包括机器学习，CV，NLP，推荐，开发等，欢迎大家star	54	Established	3,565	—
3	jackaduma/awesome_LLMs_interview_notes LLMs interview notes and answers:该仓库主要记录大模型（LLMs）算法工程师相关的面试题和参考答案	51	Established	1,310	—
4	whaleonearth/MLE-DS-Interview-Prep-Guide This repo is meant to serve as a detailed guide for Machine Learning/AI interviews.	49	Emerging	288	—
5	Picovoice/pico-cookbook Recipes for on-device voice AI and local LLM	47	Emerging	107	C
6	wdndev/llm_interview_note 主要记录大语言大模型（LLMs）算法（应用）工程师相关的知识及面试题	40	Emerging	13,130	HTML
7	ningg/Machine-Learning-Q-and-AI 大模型技术30讲（原版），30 Essential Questions and Answers on Machine Learning and AI，百面大模型	40	Emerging	29	Python
8	chensi-cs/LLM-Interview-Guidebook 本仓库是一份面向大模型算法工程师的面试宝典，系统梳理了大模型的核心知识点，帮助读者快速掌握大模型面试中的重点和难点	36	Emerging	45	—
9	Joining-AI/LLM_Interview_Prepare 本仓库是关于大模型面试中常见面试试题和面试经验的整理。这里收集了各类与大模型相关的面试题目，并提供详细的解答和分析。本仓库由上海交大交影社区维护	35	Emerging	119	HTML
10	AIR-hl/llm-interview-code LLM面试常见手撕合集	34	Emerging	248	Jupyter Notebook
11	sreekanth-madisetty/Awesome-LLM-Interview-Questions A curated collection of interview questions and expert answers focused on...	28	Experimental	16	—
12	FredericVAN/LLM-Coding-Interview-tutorial LLM Coding Interview Preparation 手撕代码系列	24	Experimental	2	Jupyter Notebook
13	krish-mm/cookbookLM An Open Source alternative of Google's NotebookLM	24	Experimental	3	TypeScript
14	Harsh-Avinash/Caduceus Infinite power but in a pendrive	23	Experimental	4	Jupyter Notebook
15	CycloneBoy/llm_interview llm interview skills 大模型面试技能	23	Experimental	2	HTML
16	bnovik0v/llm-interview-questions 430 technical interview questions with answers for LLM Researcher, LLM...	22	Experimental	—	—
17	shaoxueheng/AI-LLM-Practice AI大模型实战：从零基础到项目落地	22	Experimental	1	HTML
18	DolbyUUU/Awesome-LLM-Interview-Questions-and-Answers 大模型算法工程师、大模型Agent开发工程师面试：常见题目和答案	20	Experimental	30	—
19	Greebbie/LLM-Agent-Core_Concept_Code Designed essential LLM course for zero to LLM, a tutorial to follow up....	19	Experimental	6	Jupyter Notebook
20	Lvyizhuo/Alibaba-ACACertification-LLM 阿里云大模型工程师 ACA 认证-教程-笔记-思维导图	15	Experimental	1	HTML
21	pchemguy/LLM101 Notes on LLM learning.	14	Experimental	—	—
22	Adarsh-Khatri/ai-ml-interview-prep Structured AI/ML/LLM interview preparation with in-depth explanations and intuition	14	Experimental	—	—
23	sudhanshukuumar/LLM-Algorithm-Intern-Guide 📚 Enhance your interview preparation for LLM algorithm internships with...	13	Experimental	—	—
24	California3/NLPer-Interview-master 算法岗-自然语言处理-大语言模型-应试资料	12	Experimental	6	Jupyter Notebook
25	yyb345/interview_notes 大数据+AI+后端技术体系笔记	11	Experimental	1	Java

Comparisons in this category

awesome_LLMs_interview_notes and llm_interview_note (51 vs 40) llm_interview_note and llm_interview (40 vs 23) LLM-Interview-Questions-and-Answers-Hub and awesome_LLMs_interview_notes (56 vs 51) awesome_LLMs_interview_notes and LLM_Interview_Prepare (51 vs 35) awesome_LLMs_interview_notes and LLM-Interview-Guidebook (51 vs 36) awesome_LLMs_interview_notes and Awesome-LLM-Interview-Questions-and-Answers (51 vs 20) awesome_LLMs_interview_notes and Awesome-LLM-Interview-Questions (51 vs 28) awesome_LLMs_interview_notes and llm_interview (51 vs 23) LLM-Interview-Questions-and-Answers-Hub and Awesome-LLM-Interview-Questions-and-Answers (56 vs 20) LLM-Interview-Questions-and-Answers-Hub and Awesome-LLM-Interview-Questions (56 vs 28)