Common Interview Questions for Large Model Positions — A Practical Guide

Lately, large language models have become a big deal across many industries, and interviews for related roles in North America have gotten more detailed and professional. For international students, besides just technical skills, interviewers really pay attention to your communication, how well you understand projects, and your ability to break down problems. Instead of memorizing canned answers, it’s way better to focus on really grasping the basics and how they fit into real situations.

The questions you’ll often get are about how Transformers work — stuff like how Self-Attention actually operates, why we need Position Encoding, and what Layer Normalization does inside the model. Sometimes, interviewers dig deeper and ask how different parts connect, like what the Feedforward layer does or why Residual Connections help train deeper networks. If you only give a shallow answer, they’ll probably keep asking, so knowing the math and reasoning behind it helps a lot.

You’ll also get questions about real project experience — like “How did you pick the model for your project?”, “Why choose GPT over BERT?”, or “How do you handle noisy data?” These aren’t about showing off fancy techniques, but about showing you can think through what fits best for the task. If you can talk about your own projects, that feels more natural and believable.

Sometimes, interviewers throw in open-ended questions like “What do you think are the limitations of large models today?” or “Where do you see future improvements in LLMs?” There’s no right or wrong here — it’s more about your thought process and how clearly you express it. You can mention recent trends like LoRA, MoE, or Instruction Tuning to show you’re keeping up, even if just at a high level.

One last thing — communication matters a lot. Companies in North America really value someone who can explain complex ideas clearly and simply. Often, that’s even more impressive than knowing every tiny technical detail. Interviews aren’t just about testing your skills — they want to see if you’ll work well in a team and handle real problems. So practicing how to talk about your projects, explain ideas, and share your thinking is way more useful than just grinding coding problems.