The interview process began with a Hiring Manager (HM) call and a recruiter call, followed by a week of four-round onsite interviews. These included standard components such as Machine Learning (ML), behavioral, and coding assessments. I would describe the difficulty as moderate, a sentiment echoed by others. Notably, unlike some companies, they did not ask "hard" LeetCode questions. I cannot provide further specifics due to signing a Non-Disclosure Agreement (NDA). The entire process spanned approximately a month and a half.

The outcome was a rejection. The recruiter and HM clearly communicated that my interview performance was strong, and the primary reason for rejection was the high level of competition. Other candidates simply possessed more relevant experience. I feel that if experience was going to be the deciding factor, they should have rejected my application at the resume stage, which would have saved time for everyone involved.

That being said, the individuals I interacted with were very pleasant, and the process and interview expectations were clearly communicated. This was my first Machine Learning Engineer (MLE) interview after graduate school, making it a valuable learning experience. My advice for anyone interviewing is to carefully review all materials provided by the recruiter.

What was your research area?