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AIMLInterviews

From public sources

A Comprehensive Guide for Generative AI, Agentic AI, Multimodal AI, Physical AI Interviews. Proven Formula for multiple FAANG offers and more

AI toolCategory: AI AgentsOpen sourcedata checked Oct 16, 2026
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Overview

  • agentic
  • ai
  • ai-agents
  • ai-engineering
  • deep-learning
  • interview
  • interview-practice
  • interview-preparation
  • interviews
  • machine-learning
  • machine-learning-algorithms
  • scalable-applications

Installation

Commands are shown, never run by the marketplace. Check them against the official documentation.

Compatibility

Unknown means no evidence was found — not that the product is incompatible.
PlatformStatusArchitectureEvidenceConfidence
WindowsUnknown———
macOSUnknown———
LinuxUnknown———
Web browserUnknown———
Server / self-hostedUnknown———
Container (OCI)Unknown———

Releases

checked Oct 30, 2026
No releases found on the source.

Quality profile

algorithm quality-v1.0 · assessed Oct 16, 2026
Quality Score81
Risk Score0
Confidence 1.00
Quality Score and Risk Score are different measures. A high score does not guarantee safety.

Score components

Maintenance · 2020
last activity 7 days ago
Documentation · 1515
README 4953 chars, description present
Ready to use · 159
install instructions: yes; releases: no
Metadata · 1010
4/4 of description, homepage, license, topics
Releases · 102
0 release(s)
Category confidence · 105
classifier confidence 0.5
Adoption · 1010
9862 stars (log-dampened, 10k = max)
License clarity · 55
SPDX MIT
Community · 55
issues enabled, 1723 forks

License

MIT
Known licensefrom the repository host

This is the catalog policy status, not legal advice.

Sources

github.com/alirezadir/AIMLInterviewsPrimary★ 9,862 starslast activity Oct 8, 2026Primary repository · Confidence 1.00

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README

From alirezadir/AIMLInterviews · license MIT · fetched Oct 30, 2026

English | 简体中文 | فارسی

[License: MIT] [Code style: black] [GitHub stars] [GitHub forks] [Last Commit] [GitHub issues] [Contributors] [Tweet]

News

:newspaper: This repository is now AIMLInterviews, updated for 2026 with expanded LLM, multimodal AI, post-training, and GenAI system-design content.

AIMLInterviews 1:1 Coaching & Mock Interviews

I 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.

Topics include technical interviews (AI/ML system design, GenAI & Agentic AI fundamentals, ML fundamentals, AI coding, and more), behavioral interviews, and leadership interviews.

Learn more: https://aimlinterviews.io

AI / Machine Learning Interviews :robot:

This 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).

Remember: Interviewing is a skill and the more skillful you are, the better the results will be.

The 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:

ChapterContent
Chapter 1DSA Coding (LeetCode style)
Chapter 2ML Coding
Chapter 3ML Breadth (classic ML, Gen AI, Agentic AI)
Chapter 4System Design (classic ML, Gen AI, Agentic AI)
Chapter 5Behavioral & Leadership
ResourcesGenAI Learning Resources
ResourcesAgentic AI Systems
AI TutorAIMLInterviews MCP Server

AI Tutor with MCP

Turn 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.

claude mcp add aimlinterviews -- npx -y aimlinterviews-mcp
# or
codex mcp add aimlinterviews -- npx -y aimlinterviews-mcp

Clone this repository first, then run the command from the clone or set AIMLINTERVIEWS_ROOT. See the MCP server guide for configuration, tools, and development instructions.

Notes:

  • 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.

  • 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.

Contribution

  • Feedback and contribution are very welcome :blush: If you'd like to contribute, please make a pull request with your suggested changes).
Open the repository ↗