Ge Global Research AI Research Scientist Interview Guide

I applied online and didn’t hear back for about two months, so the process started off a little slow. Once it moved, it was pretty structured: an initial HR phone screen, then a technical phone interview with the lab manager. That technical screen was the part I was warned about, and it lived up to the reputation. Instead of a standard coding question with one clean answer, I was given a difficult programming problem that felt more realistic and open-ended, and I had to talk through how I would approach it rather than just produce a textbook solution. It was definitely more about judgment and problem framing than memorizing an algorithm.

After that, the onsite was much broader. I gave a one-hour presentation on my research projects, and the team spent a lot of time asking questions about the work itself, including what I was most proud of and why I made certain choices. The questions were thoughtful and, in my case, the team members seemed genuinely curious and even offered a few useful suggestions. I also had separate conversations with the team manager, an adjacent lab manager, a technology leader, and finally HR. The manager and HR rounds were more behavioral and future-focused, with questions about why I wanted to join and where I saw myself in five years. The adjacent lab manager was the toughest of the later rounds, while the technology leader stayed more high-level and big-picture. Overall, it felt like a selective process with relatively few technical questions on the onsite, but a lot of emphasis on communication, research depth, and fit. I ended up not getting an offer, so I’d say the main takeaway is to be ready for an open-ended technical screen and to prepare a very solid research presentation with clear answers about your past work and long-term goals.