Process
Ask me about past experience and LeetCode medium-level questions.
However, the interviewer closed their camera during the interview, which made me uncomfortable.
I spent 30 minutes on the coding question. The interviewer said I had a mistake, but I couldn't figure it out.
Questions
Why did I use a model instead of others?
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Interview Statistics
The following metrics were computed from 125 interview experiences for the TikTok Machine Learning Engineer role in United States.
Success Rate
9%
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
Positive34%
Neutral46%
Negative20%
Candidates reported having good feelings for TikTok's Machine Learning Engineer interview process in United States.
TikTok Work Experiences
4.0
Fast Learning, Challenging Wlb
Machine Learning Engineer • Current Employee
San Jose, California, United States
August 29, 2025
Pros: Learn a lot, very fast-paced.
Cons: Bad work-life balance and lack of organization.
5.0
Great Team, Tough Pressures
Machine Learning Engineer • Current Employee
San Jose, California, United States
February 27, 2025
Pros: Team is great, strong management, and very interesting technical problems.
Cons: Concerns with governmental pressures.
3.0
Learned Fast, Toxic Culture
Machine Learning Engineer • Current Employee
Singapore, Singapore
September 2, 2025
Pros: Fast-paced learning and exposure to large-scale systems.
Cons: Politics, favoritism, bias, toxicity, insulting.
- 4.0Fast Learning, Challenging WlbMachine Learning Engineer • Current EmployeeSan Jose, California, United StatesAugust 29, 2025Pros: Learn a lot, very fast-paced.Cons: Bad work-life balance and lack of organization.
- 5.0Great Team, Tough PressuresMachine Learning Engineer • Current EmployeeSan Jose, California, United StatesFebruary 27, 2025Pros: Team is great, strong management, and very interesting technical problems.Cons: Concerns with governmental pressures.
- 3.0Learned Fast, Toxic CultureMachine Learning Engineer • Current EmployeeSingapore, SingaporeSeptember 2, 2025Pros: Fast-paced learning and exposure to large-scale systems.Cons: Politics, favoritism, bias, toxicity, insulting.
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