Apple Machine Learning Engineer interview experience

In one of my technical rounds, I ended up focused on a recommendation-style problem in music: figuring out user intent in typing-related recommendations across songs, albums, and artists, and explaining how to evaluate those predictions using A/B testing. That felt very applied and tied directly to what the team built.

In another track that also felt domain-heavy, the process largely revolved around my project experience and relevant technologies instead of heavy live coding. HR had suggested there could be on-demand coding, but the interviews emphasized how I’d handled video or image