Machine Learning Engineer applicants have rated the interview process at TikTok with 4 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 50% positive. To compare, the company-average is 38.2% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 1 day to get hired, when considering 2 user submitted interviews for this role. To compare, the hiring process at TikTok overall takes an average of 26 days.
Common stages of the interview process at TikTok as a Machine Learning Engineer according to 2 Glassdoor interviews include:
Presentation: 33%
One on one interview: 33%
Drug test: 33%
Here are the most commonly searched roles for interview reports -
Surprisingly straightforward — I expected a tougher challenge for a machine learning role. After a quick recruiter screen, the first technical round focused on implementing K-means clustering, which felt familiar. Handling edge cases for empty clusters was tricky, though. What really helped me prep were the algorithm explanations on PracHub, which gave me confidence going in. The final interviews were a mix of problem-solving and behavioral questions, and in the end, I received an offer that I accepted. Overall, it was a decent experience.
Interview questions [1]
Question 1
implementing K-means clustering from scratch and handling empty cluster edge cases
I applied through university. I interviewed at TikTok in Oct 2025
Interview
Asked about past projects and work experience in detail. Merge sort, a Medium-Hard DP problem. A case problem with designing a model to recommend items for tiktok shop. Interview was in Chinese.
Interview questions [1]
Question 1
Compute numbers of ways you can put N queens on a N*N chess table.
I applied through a recruiter. The process took 1 week. I interviewed at TikTok (San Jose, CA) in Mar 2026
Interview
one hour first round tiktok usds phone screen interview. past projects questions, leetcode mid questions, and machine learning, deep learning, large language model questions. And then ask the interviewer questions.