Machine Learning Engineer Interview Experience - San Jose, California
September 22, 2026
Negative ExperienceGot Offer
Process
The process was three rounds.
- Round 1: One LeetCode question regarding linked lists and a resume deep dive.
- Round 2: A resume deep dive, one probability question, and one medium LeetCode problem.
- Round 3: Mostly a high-level resume deep dive.
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Interview Statistics
The following metrics were computed from 29 interview experiences for the TikTok Machine Learning Engineer role in San Jose, California.
Success Rate
24%
Pass Rate
TikTok's interview process for their Machine Learning Engineer roles in San Jose, California is very selective, failing most engineers who go through it.
Experience Rating
Positive31%
Neutral48%
Negative21%
Candidates reported having good feelings for TikTok's Machine Learning Engineer interview process in San Jose, California.
TikTok Work Experiences
3.0
Machine Learning Engineer 2-1
Machine Learning Engineer • Former Employee
San Jose, California, United States
March 26, 2024
Pros: 25% target bonus, which is higher than average.
Cons: Work-life balance is not great.
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 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.
- 3.0Machine Learning Engineer 2-1Machine Learning Engineer • Former EmployeeSan Jose, California, United StatesMarch 26, 2024Pros: 25% target bonus, which is higher than average.Cons: Work-life balance is not great.
- 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 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.
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