Process
Two rounds of technical interviews and one round of behavioral questions were conducted.
The overall difficulty was medium.
The main topics included:
- Walking through the resume
- Discussing one of the projects
- A coding test
Overall, it was a very nice experience.
Questions
Describe one of the projects you have done.
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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
5.0
Great Tech, Math Heavy
Machine Learning Engineer • Current Employee
San Jose, California, United States
October 20, 2025
Pros: The team is excellent, with a very modern tech stack. Candidates are expected to have strong data sensitivity and the ability to perform both online and offline data analysis and reasoning across the entire data and model pipeline. Of course, coding requirements are also high, especially for high-performance systems such as those built in C++.
Cons: Of course, a large part of the work involves solving problems through data analysis and modeling them using appropriate statistical and mathematical methods. Therefore, if someone is uncomfortable with mathematics, this role may not be a good fit.
5.0
Great place for making impacts
Machine Learning Engineer • Former Employee
Seattle, Washington, United States
April 9, 2025
Pros: A fast-moving culture promotes rapid development and experimentation, and you can propose and execute end-to-end projects with minimal red tape.
Cons: The rapid deployment of projects leads to a lack of overall engineering rigor and mentorship. Lots of ML knowledge can be half-baked, and results are not understood well.
2.0
Better be able to speak Mandarin
Machine Learning Engineer • Current Employee
San Jose, California, United States
April 29, 2024
Pros: You can only speak Mandarin at work.
Cons: It's hard to work here without speaking Mandarin.
- 5.0Great Tech, Math HeavyMachine Learning Engineer • Current EmployeeSan Jose, California, United StatesOctober 20, 2025Pros: The team is excellent, with a very modern tech stack. Candidates are expected to have strong data sensitivity and the ability to perform both online and offline data analysis and reasoning across the entire data and model pipeline. Of course, coding requirements are also high, especially for high-performance systems such as those built in C++.Cons: Of course, a large part of the work involves solving problems through data analysis and modeling them using appropriate statistical and mathematical methods. Therefore, if someone is uncomfortable with mathematics, this role may not be a good fit.
- 5.0Great place for making impactsMachine Learning Engineer • Former EmployeeSeattle, Washington, United StatesApril 9, 2025Pros: A fast-moving culture promotes rapid development and experimentation, and you can propose and execute end-to-end projects with minimal red tape.Cons: The rapid deployment of projects leads to a lack of overall engineering rigor and mentorship. Lots of ML knowledge can be half-baked, and results are not understood well.
- 2.0Better be able to speak MandarinMachine Learning Engineer • Current EmployeeSan Jose, California, United StatesApril 29, 2024Pros: You can only speak Mandarin at work.Cons: It's hard to work here without speaking Mandarin.
TikTok Interview Questions
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