Machine Learning Engineer Interview Experience - San Jose, California
November 6, 2025
Neutral ExperienceNo Offer
Process
Apply online.
HR screening call (30 minutes), asking about your interest and past experiences and introducing different teams.
Two tech interviews (60 minutes each).
- Past projects deep dive
- Statistics questions
- LeetCode
Questions
Explain PPO, loss function of DPO.
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Interview Statistics
The following metrics were computed from 23 interview experiences for the TikTok Machine Learning Engineer role in San Jose, California.
Success Rate
26%
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
Positive35%
Neutral48%
Negative17%
Candidates reported having good feelings for TikTok's Machine Learning Engineer interview process in San Jose, California.
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 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.
4.0
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.
- 5.0Great 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, 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.
- 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.
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