Snap·Machine Learning Engineer

Snap Machine Learning Engineer interview experience

No offer

Hard

Negative

United StatesPosted Mar 2024 · Candidate report, summarized by Dataford

My most difficult technical step was a phone screen that felt unusually advanced and also hard to communicate through.

The round was split into three parts: values (behavioral), coding, and applied ML. In coding, I was asked a tough LeetCode-style problem about getting the median from two sorted arrays.

Then the applied ML portion pushed into attention mechanisms—I had to explain an attention layer. Even beyond the difficulty of the questions themselves, the experience felt off: it came across as advanced for an MLE screen, and the interviewer’s communication made it much harder to get to solid footing. When I tried to answer, the conversation didn’t flow well and it felt like even basic questions weren’t

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