Pinterest Machine Learning Engineer interview: ML theory and quick rejection

The loop was short but rough. In the initial conversation, I tried to explain my projects, but the interviewer did not seem willing to listen. I then had a technical machine-learning session covering core theory, including vanishing gradients and ensemble methods such as bagging and boosting.

There was also a LeetCode-style problem for about 30 minutes. The process ended quickly, and I received an HR rejection roughly half an hour after the interview.

The result was not the only difficult part. The early tone put me on edge, and I felt I had not been given a fair chance to communicate clearly.

Location: Palo Alto, CA. Overall feedback: negative. Offer status: no offer.