Interview prep that treats AI roles as different species

What it does

This repository buckets AI interview questions into five role-specific tracks: AI Engineer, ML Engineer, AI Researcher, Data Scientist, and AI Architect. Rather than generic memorization drills, it frames each track around a distinct thinking pattern—production reliability for engineers, theoretical novelty for researchers, and so on. The aim is to get you reasoning out loud about trade-offs instead of reciting canned answers.

The interesting bit

The structure treats interview prep as mindset calibration, not fact ingestion. By organizing content around how a role thinks—“How do I make this work reliably in production?” versus “Why does this work, and what’s fundamentally new?"—it forces you to context-switch before the hiring manager does.

Key highlights

• Five clearly separated tracks with distinct “thinking patterns” rather than just topic tags
• Explicit focus on system thinking, trade-off awareness, and communication skills
• 1,021 stars suggest the community finds the role-first angle useful
• Organized to highlight how the same concept gets interrogated differently across roles

Caveats

• The README outlines philosophy and folder structure but never shows actual questions or answers, so content depth is unclear without opening the folders
• No language or topic metadata, confirming this is a document collection rather than tooling

Verdict

Worth bookmarking if you are targeting a specific AI role and need to calibrate your answers to the right altitude. Skip it if you want a single generic study guide or executable code.