Four interviews: 1. 15m call with in-house recruiter about role. 2. 1h no coding problem solving interview. I was given a deep learning case study and had to talk about how I'd go about solving it. 3. 1h programming interview. Data structures and algorithms. 4, 1h PyTorch debugging interview. I was given a Google colab notebook which trained a CNN, and I had to debug errors.

I had an introductory call with the recruiter, and it seemed like they were hiring for multiple teams—such as the data team, model team, etc. From the conversation, it felt like the recruiter understood my strengths and decided to move me forward to the next stage. I then had two one-hour interviews: one focused on machine learning and the other on ML system design. I believe I answered the questions reasonably well and was optimistic about progressing further. However, two days later, I was informed that Wayve did not see a direct match between my skill set and their current requirements. They mentioned it would be good to stay in touch in case things change in the future. While I enjoyed the interview process and found it to be a good learning experience, I found the outcome a bit disorganized. It’s surprising that a mismatch in skill set wasn’t identified earlier, especially since one of the key responsibilities of a recruiter is to ensure alignment before moving candidates forward in the process. Additionally, I didn’t receive any feedback from the interviewers, which is disappointing—as it would have been helpful to understand what went well and where I could improve.