{"data":{"slug":"alirezadir-machine-learning-interviews","name":"Machine-Learning-Interviews","tagline":"Guide for Machine Learning/AI technical interviews","github_url":"https://github.com/alirezadir/Machine-Learning-Interviews","owner":"alirezadir","repo":"Machine-Learning-Interviews","owner_avatar_url":"https://avatars.githubusercontent.com/u/5262877?v=4","primary_language":"Jupyter Notebook","stars":9694,"forks":1695,"topics":["agentic","ai","ai-agents","ai-engineering","deep-learning","interview","interview-practice","interview-preparation","interviews","machine-learning","machine-learning-algorithms","scalable-applications","system-design"],"archived":false,"github_pushed_at":"2026-09-02T07:20:33+00:00","maintenance_label":"Active","stars_delta_30d":1056,"url":"https://www.graphcanon.com/tools/alirezadir-machine-learning-interviews","markdown_url":"https://www.graphcanon.com/tools/alirezadir-machine-learning-interviews.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/alirezadir-machine-learning-interviews","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=alirezadir-machine-learning-interviews","description":"This repo is meant to serve as a guide for Machine Learning/AI technical interviews. ","homepage_url":"https://www.aimlinterviews.io/","license":"MIT","open_issues":11,"watchers":108,"ai_summary":"Repository aimed at preparing candidates for ML/AI engineering interviews with insights and topics relevant to roles at major tech companies.","readme_excerpt":"## AIMLInterviews 1:1 Coaching & Mock Interviews\n\nI now offer **1:1 AI/ML interview coaching & mock interviews** for AI/ML Engineers, Applied AI Scientists, Research Engineers, Research Scientists, AI Strategists, Engineering Managers, and senior AI leaders.\n\nTopics include technical interviews (AI/ML system design, GenAI & Agentic AI fundamentals, ML fundamentals, AI coding, and more), behavioral interviews, and leadership interviews.\n\nLearn more: [https://aimlinterviews.io](https://aimlinterviews.io)\n\n---\n\n
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\n\nEnglish | [简体中文](README-CN.md) | [فارسی](README-FA.md)\n\n \n# AI / Machine Learning Interviews :robot: \n\nThis repo aims to serve as a guide to prepare for **AI and ML Technical interviews** for relevant roles at big tech companies (in particular FAANG). It has compiled based on the author's personal experience and notes from his own interview preparation, when he received 5 simultaneous offers from Meta (ML Specialist), Google (ML Engineer), Amazon (Applied Scientist), Apple (Applied Scientist), and Roku (ML Engineer) in 2020, and repeated offers from Amazon and Apple in 2025 (AI Tech Lead).\n\n> **Remember:** Interviewing is a skill and the more skillful you are, the better the results will be.\n\nThe following components are the most commonly used interview modules for technical ML roles at different companies. We will go through them one by one and share how one can prepare:\n\n
\n\n## AI Tutor with MCP\n\nTurn any MCP-compatible AI assistant into an AI/ML interview coach with `aimlinterviews-mcp`. It discovers curriculum problems, offers progressive hints, builds learning and company preparation plans, and reviews answers using a no-spoilers teaching style.\n\n```bash\nclaude mcp add aimlinterviews -- npx -y aimlinterviews-mcp\n# or\ncodex mcp add aimlinterviews -- npx -y aimlinterviews-mcp\n```\n\nClone this repository first, then run the command from the clone or set `AIMLINTERVIEWS_ROOT`. See the [MCP server guide](MCP/README.md) for configuration, tools, and development instructions.\n\n## News\n\n:newspaper: This repository is now **AIMLInterviews**, updated for 2026 with expanded LLM, multimodal AI, post-training, and GenAI system-design content.\n\n**Notes:**\n* AI and ML interviews at different companies do not follow a unique structure. However, I found the components very similar across FAANG companies. Startup interviews are often tailored to their own use cases and problems at hand, while larger companies tend to follow a more consistent structure.\n\n* The guide here is mostly focused on *AI / ML Engineering, Applied Science, Tech Lead* roles at big companies. Although relevant roles such as \"Data Science\" or \"Research scientist\" have different structures in interviews, some of the modules reviewed here can be still useful. \n\n\n# Contribution\n* Feedback and contribution are very welcome :blush: \n**If you'd like to contribute**, please make a pull request with your suggested changes).","github_created_at":"2021-01-31T03:52:09+00:00","created_at":"2026-07-07T17:41:27.713443+00:00","updated_at":"2026-09-20T06:58:32.45476+00:00","categories":[{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"agentic-ai","name":"agentic-ai"},{"slug":"llms","name":"llms"},{"slug":"machine-learning-algorithms","name":"machine-learning-algorithms"},{"slug":"ml-interview-guide","name":"ml interview guide"},{"slug":"system-design","name":"system design"}],"trust":{"provenance":{"is_fork":false,"github_id":334567245,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T06:58:30.517Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":17,"last_release_at":null,"stars_delta_30d":1056,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-09T11:35:57.240Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T06:58:31.714Z"},"languages":{"value":["jupyter notebook"],"source":"github.language","observed_at":"2026-09-20T06:58:31.714Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-20T06:58:31.714Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"The repository itself is free under the MIT license but offers supplementary 1:1 AI/ML coaching services at an additional cost, which is outlined on https://aimlinterviews.io"},"requirements":{"notes":["- Python and Jupyter Notebook knowledge for interacting with the material.","- Basic to advanced understanding of ML concepts to grasp the depth covered in the repository."]},"constraints":{"pricing_model":"freemium"},"when_to_use":["- You are targeting roles such as Machine Learning Engineer or Applied Scientist positions at major tech companies like FAANG.","- You need to prepare for updates in ML/AI interviews covering advanced topics, including LLMs and multimodal AI.","- You require specific preparation for GenAI system design with chapters dedicated to RAG, agents, guardrails, and evaluation.","- You are interested in insights that align with the experiences of someone who has been through the interview process at FAANG companies."],"when_not_to_use":["- If your focus is on roles such as Data Science or ML research scientist where the structure of interviews differs significantly from Machine Learning Engineer positions.","- For candidates who do not aim to work at big tech companies but rather in startups or smaller organizations, as this tool emphasizes preparation for FAANG and similar entities.","- If you are looking for general developer tools that cover a wide range of programming languages and frameworks beyond ML-related content."],"source":"enrich:decision_facts","observed_at":"2026-07-09T08:03:03.056Z"},"constraint_facets":{"pricing_model":"freemium"},"decision_summary":[{"label":"Pricing","value":"freemium - The repository itself is free under the MIT license but offers supplementary 1:1 AI/ML coaching services at an additional cost, which is outlined on https://aimlinterviews.io"},{"label":"Requirements","value":"- Python and Jupyter Notebook knowledge for interacting with the material.; - Basic to advanced understanding of ML concepts to grasp the depth covered in the repository."},{"label":"Adopt for","value":"Machine-Learning-Interviews is aimed at candidates preparing for technical ML/AI interviews, focusing on deep topics including LLM internals and GenAI system design. Here are critical facts for decision making about its适"}]}}
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