Process
Questions cover implementing Breadth-First Search (BFS).
There was also a coding question using a priority queue (the exact question wasn't remembered).
The technical question included understanding BERT in machine learning, including how it is trained and its model architecture.
Questions
Did you know anything about BERT?
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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
3.0
Good Learning, Bad Balance
Machine Learning Engineer • Current Employee
Mountain View, California, United States
July 11, 2021
Pros: You can learn things there.
Cons: Bad work-life balance there.
4.0
Comfortable, Growing, Lacking Diversity
Machine Learning Engineer • Former Employee
San Jose, California, United States
July 22, 2024
Pros: A comfortable environment and a rapidly growing business.
Cons: A large amount of the employees are Chinese, a little bit bad in diversity.
4.0
A place where your work makes a real impact
Machine Learning Engineer • Former Employee
San Jose, California, United States
August 26, 2025
Pros: With a large user base and a small team, your work can make a real impact.
Cons: Not so much guidance.
Offices are located across the globe, and they work across different time zones.
- 3.0Good Learning, Bad BalanceMachine Learning Engineer • Current EmployeeMountain View, California, United StatesJuly 11, 2021Pros: You can learn things there.Cons: Bad work-life balance there.
- 4.0Comfortable, Growing, Lacking DiversityMachine Learning Engineer • Former EmployeeSan Jose, California, United StatesJuly 22, 2024Pros: A comfortable environment and a rapidly growing business.Cons: A large amount of the employees are Chinese, a little bit bad in diversity.
- 4.0A place where your work makes a real impactMachine Learning Engineer • Former EmployeeSan Jose, California, United StatesAugust 26, 2025Pros: With a large user base and a small team, your work can make a real impact.Cons: Not so much guidance. Offices are located across the globe, and they work across different time zones.
TikTok Interview Questions
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