When applying for jobs in North America, especially as an international student majoring in computer science, interviewing at OpenAI is both a rare chance and a high-pressure experience. The company is one of the leaders in the AI industry, and its interviews are known to be technical, deep, and very thoughtful. It’s not only about how you code, but how you break down a problem and explain your decisions clearly.
Usually, the first round comes as a virtual screening. You’ll get several coding problems. Even though they might seem similar to what you find on platforms like LeetCode, the difference is they often reflect real engineering scenarios—like improving system efficiency, handling large data sets, or building a simple version of a tool. In these situations, it’s not just about writing code that passes tests, but also about clearly explaining your logic and making sure the interviewer can follow your process. That part can be especially tricky for international students if English is not their first language, so practicing how to talk through a problem out loud is something I found very useful.
If you make it through, the next rounds dig deeper. You might be asked questions on system design, infrastructure, or AI-related topics depending on the role. If it’s for an engineering position, you might need to design a backend service that scales well and keeps data secure. If you’re applying for a research position, you’ll likely discuss architecture-level questions, like how transformers function or what improvements you think future models might need. Sometimes they’ll ask what you thought about a recent research paper or challenge your understanding of AI ethics.
Besides coding, OpenAI also wants to see how you think beyond the screen. In behavioral interviews, they often ask about how you view AI’s role in society, or if you’ve dealt with ethical questions in past projects. Communication and collaboration also come up a lot, and you’re expected to show that you can work with people from different backgrounds. I personally had to reflect on group projects from school and explain what I did when a team didn’t agree on a solution.
For preparation, brushing up your coding is just one part. I spent time reading OpenAI’s blog, papers, and job descriptions to better understand what they care about. Then I tried to link that to my own experience. Being able to show that you understand the company and how you could contribute helps set you apart.
In the end, even if you don’t get the offer, the process itself helps you grow. You learn a lot about your technical level, how to communicate better, and what kind of engineer you want to become.
Release time:2025-06-03
