AIMLInterviews is a guide and preparation resource for machine learning and AI technical interviews at major technology companies.
The resource addresses the challenge of preparing for ML and AI technical interviews by organizing preparation into distinct modules covering the skills typically assessed. It structures interview preparation around six main components: general coding and data structures, ML-specific coding, ML fundamentals including classical machine learning and large language models, ML and GenAI system design, agentic AI systems, and behavioral interviews. The approach draws from the author's personal interview experience and notes accumulated during preparation for roles at major companies.
Developers and engineers preparing for ML and AI roles at large technology companies should consider this resource, particularly those targeting FAANG companies where interview structures tend to follow consistent patterns. The guide suits candidates preparing for positions such as ML Engineer, Applied Scientist, Research Engineer, or AI Tech Lead roles. The resource includes practical components like coding problem sets, system design frameworks, and behavioral interview preparation worksheets. An AI tutor powered by Model Context Protocol integration allows users to turn compatible AI assistants into interview coaches that provide progressive hints and personalized learning plans without revealing answers directly.
The project maintains active development with recent updates expanding coverage of large language models, multimodal AI, post-training techniques, and GenAI system design content. The repository includes structured chapters with linked resources, a dedicated MCP server implementation for AI-assisted tutoring, and supplementary materials such as Google Sheets and Excel templates for behavioral and leadership interview preparation. The codebase is primarily organized as Jupyter Notebooks, supporting interactive learning and hands-on practice with code examples.
