Interviewing for AI Roles: What They Actually Test

You studied machine learning theory. That's not what they're testing. Here's what actually matters.

The Rounds You'll Face

Technical screening (30-45 min): Code a function (usually non-AI related). Implement binary search, reverse a linked list. Same as any software engineer role. Standard leetcode medium.

System design (45-60 min): Design a RAG system or LLM feature. They want to see: can you think about trade-offs? Do you know what technologies to use? Can you communicate clearly?

AI depth (30-45 min): Discuss a paper you've read or a project you've built. Explain what you'd do differently. This is where your actual knowledge matters.

Behavioral: Same as any company. Tell stories about conflicts, failures, impact.

What They're Really Testing

System thinking:

• Can you decompose a problem?
• Do you ask clarifying questions?
• Can you discuss trade-offs (cost vs latency, quality vs speed)?

Relevant knowledge:

• Do you know what RAG is and why it's useful?
• Have you thought about vector databases, embeddings, prompt engineering?
• Can you articulate why fine-tuning might not be the right answer?

Communication:

• Can they follow your thinking?
• Do you explain decisions or just state them?
• Can you handle pushback and adjust?

Honesty:

• Do you admit when you don't know something?
• Can you say "that's a trade-off I'd need to measure"?

What They're NOT Testing

• Deriving backprop from first principles
• Writing CUDA kernels
• Knowing every architecture detail
• Transformer math
• Every new model that dropped last week

Most companies have an ML researcher onboard if they need that level of depth. They're hiring engineers to build, not research.

How to Prepare

For technical round: 1-2 weeks of leetcode medium problems. Nothing special.

For system design:

• Design RAG systems (retrieval, ranking, generation)
• Design a fine-tuning pipeline
• Design an evaluation framework
• Think about cost and latency
• Use real examples (what did you build?)

For AI depth:

• Pick something you've built or a paper you've read
• Be able to explain it to a PhD and a non-technical person
• Articulate what you'd change
• Ask questions back

For behavioral:

• Prepare 4-5 stories about impact, failure, learning
• Practice 2-minute versions

Most engineers interview the same everywhere. These fundamentals transfer. You've got this.