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Machine Learning Engineer Interview Experience - United States

September 1, 2025
Neutral ExperienceNo Offer

Process

I applied online through a job board site for the San Jose office. The process took a little over two months, and I had six rounds of interviews.

  • First round: The first 45 minutes were spent discussing my PhD research, with the last 15 minutes featuring a medium LeetCode question (longest increasing subsequence problem).
  • Second round: The first 30 minutes focused on my PhD research. The last 30 minutes were dedicated to an ML design question: "How to filter out gun violence from TikTok videos?"
  • Third round: Similar to the second, the first 30 minutes covered my PhD research. The latter 30 minutes involved an ML design question: "How to determine whether a hashtag is relevant to a video or not?"
  • Fourth round: This was an HR interview lasting approximately 30 minutes, covering basic behavioral questions such as "How do you handle harsh criticism?" The interviewer mentioned that they had a tight headcount and that they would provide an update within a week or two.

I was then contacted by two other HR members who informed me that my profile had been noticed by two additional leaders, and I would have two more interview rounds. My understanding is that the role for the original team (safety and trust) had been filled, and the search team was now interested in interviewing me.

  • Fifth round interview: The TLM of the search team was the interviewer. The first 25 minutes were spent describing my PhD research, followed by 45 minutes on an ML design question: "How would you determine from a large set of sparse features which ones are the most important to use for predicting CTR on a TikTok video?"
  • Sixth round interview: The Head of Search, USDS, was the interviewer. This was presented as a "behavioral round," but it felt more like an opportunity to sell myself on why I should work on the search team. One question asked was: "How would you handle a deadline that you couldn't make?"

Overall, the interview experience took an incredibly long time, and it was difficult to understand why I wasn't matched to either team in the end. That being said, each interviewer was polite, clear, and helpful during the interviews.

Questions

Longest Increasing Subsequence LeetCode problem

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Interview Statistics

The following metrics were computed from 113 interview experiences for the TikTok Machine Learning Engineer role in United States.

Success Rate

8%
Pass Rate

TikTok's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.

Experience Rating

Positive36%
Neutral44%
Negative19%

Candidates reported having good feelings for TikTok's Machine Learning Engineer interview process in United States.