Solving a Real AI Engineer Take-Home Assignment Live
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What do AI engineer take-home assignments look like, and how should you approach them?
During the session, Alexey will pick one home assignment for an AI engineer role and work through it live.
He’ll show the thinking process behind it: how to interpret the task, clarify requirements, make design decisions, and balance speed with quality.
This session is based on a broader analysis of 1,765 job descriptions, 100+ GitHub repos with real candidate submissions, and practitioner reports on AI/ML engineering interview processes.
That research shows that take-home assignments are a common part of the hiring process, especially for roles involving RAG, agents, document processing, evaluation, and production-style AI systems.
What you’ll learn
- What AI engineer take-home assignments typically look like - How to break down an open-ended task - How to choose a reasonable scope and architecture - How to prioritize under time pressure - What makes a submission stronger in a real interview process
About the speaker
Alexey Grigorev is a software engineer and machine learning practitioner with 15+ years of experience building production ML systems. He focuses on practical, production-grade ML and AI systems, from early prototypes to reliable production systems.
At AI Shipping Labs, Alexey is building the kind of environment that would have accelerated my own career growth. After years of teaching at scale, he wanted something more focused: a space for action-oriented builders who want to turn AI ideas into real projects.