AI Engineering: The Interview Process

Hosted by Alexey Grigorev

Tue, Mar 3, 2026

4:00 PM UTC (1 hour 30 minutes)

Virtual (Zoom)

Free to join

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AI Engineering Buildcamp: From RAG to Agents
Alexey Grigorev
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What you'll learn

Analyze Real-World Interview Data

Identify current hiring trends and frequently asked questions based on crowdsourced candidate experiences and research.

Master Technical and Conceptual Questions

Learn how to articulate complex AI concepts and defend technical decisions regarding model selection and architecture.

Solve Live Coding Challenges

Apply your skills in real-time by writing clean, efficient code for common AI-specific technical interview tasks.

Why this topic matters

The AI interview landscape is now a "wild west" blending traditional software engineering with niche machine learning concepts. By studying real stories from platforms like Reddit and X, you eliminate the fear of the unknown. This prepares you for the professional reality of technical screenings, helping you grow from a candidate who knows AI into a professional who can prove it under pressure.

You'll learn from

Alexey Grigorev

Principal Data Scientist | Book Author | Instructor to 100k+ Students World-Wide

Founder of DataTalks.Club · Creator of the Zoomcamp Series · ML Engineer & Author


Alexey Grigorev is the founder of DataTalks.Club and the creator of the popular Zoomcamp series. With 15 years of experience in software engineering and over 12 years in machine learning, he has built and deployed large-scale ML systems at companies like OLX Group and Simplaex.


An advocate for practical, hands-on education, Alexey has taught over 100,000 students, focusing on a code-first approach to help learners build real-world skills.


In the past, he was an active participant in data science competitions. A Kaggle Master, Alexey has achieved top rankings in several challenges, including 1st place in the NIPS'17 Criteo Challenge and 2nd place in the WSDM Cup 2017: Vandalism Detection.


He is also the author of several technical books, including the widely read Machine Learning Bookcamp.

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