Process
The process was 3 rounds, consisting of 50% LeetCode and 50% ML basics.
- LeetCode: Medium-level questions that included a binary search question and a graph traversal problem.
- ML basics: Topics covered LLMs, attention, basic model structures, normalization techniques, and how to prevent overfitting.
Questions
What type of normalization is used in LLMs and why?
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Interview Statistics
The following metrics were computed from 186 interview experiences for the TikTok Machine Learning Engineer role.
Success Rate
11%
Pass Rate
TikTok's interview process for their Machine Learning Engineer roles is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive34%
Neutral42%
Negative24%
Candidates reported having good feelings for TikTok's Machine Learning Engineer interview process.
TikTok Work Experiences
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.
3.0
Good learning opportunities, but intense work
Machine Learning Engineer • Current Employee
Singapore, Singapore
May 14, 2025
Pros: Plenty of things to learn and problems to tackle.
Cons: Tech might be a bit outdated.
Work-life balance is not the best.
5.0
Great Team, Sometimes Late
Machine Learning Engineer • Current Employee
San Jose, California, United States
October 6, 2025
Pros: Great team environment with great tech stacks.
Cons: Sometimes need to respond late.
- 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.
- 3.0Good learning opportunities, but intense workMachine Learning Engineer • Current EmployeeSingapore, SingaporeMay 14, 2025Pros: Plenty of things to learn and problems to tackle.Cons: Tech might be a bit outdated. Work-life balance is not the best.
- 5.0Great Team, Sometimes LateMachine Learning Engineer • Current EmployeeSan Jose, California, United StatesOctober 6, 2025Pros: Great team environment with great tech stacks.Cons: Sometimes need to respond late.
TikTok Interview Questions
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