Machine Learning Engineer Interview Experience - San Francisco, California
June 27, 2025
Positive ExperienceNo Offer
Process
Straightforward and as transparent as possible. I wish I could share more, but I signed an NDA.
All the rounds were the same. There was no clarity the recruiter gave regarding the leveling, and I kept on asking her.
Questions
Dynamic programming question found on LeetCode.
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Interview Statistics
The following metrics were computed from 3 interview experiences for the TikTok Machine Learning Engineer role in San Francisco, California.
Success Rate
0%
Pass Rate
TikTok's interview process for their Machine Learning Engineer roles in San Francisco, California is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive33%
Neutral67%
Negative0%
Candidates reported having very good feelings for TikTok's Machine Learning Engineer interview process in San Francisco, California.
TikTok Work Experiences
4.0
Fast Growth, Poor Communication
Machine Learning Engineer • Former Employee
November 26, 2025
Pros: Fast-paced company, grown fast.
Cons: Excess cross-functional cooperation leads to low communication effectiveness.
5.0
TikTok is not all bad. It’s highly team dependent
Machine Learning Engineer • Current Employee
Singapore, Singapore
November 14, 2025
Pros: I love my team. I think at TikTok it is very, very team dependent. Some teams are horrible; some are really good. Generally, people are really smart, but some teams can have horrible work cultures, such as micromanaging your time or not respecting your off days, etc. I would say it all depends on your team. If you manage to get into a good team with a good leader, even if the work is tough, it's a lot more manageable.
Cons: The pace is definitely fast, but a good team helps to make it better. My team works hard, but we also respect off days and weekends as much as we can.
4.0
Overall acceptable, but expected poor WLB
Machine Learning Engineer • Current Employee
Singapore, Singapore
October 27, 2025
Pros: quite a lot of challenges, and the colleagues are excellent.
Cons: Need to work overtime very often and have meetings at night.
- 4.0Fast Growth, Poor CommunicationMachine Learning Engineer • Former EmployeeNovember 26, 2025Pros: Fast-paced company, grown fast.Cons: Excess cross-functional cooperation leads to low communication effectiveness.
- 5.0TikTok is not all bad. It’s highly team dependentMachine Learning Engineer • Current EmployeeSingapore, SingaporeNovember 14, 2025Pros: I love my team. I think at TikTok it is very, very team dependent. Some teams are horrible; some are really good. Generally, people are really smart, but some teams can have horrible work cultures, such as micromanaging your time or not respecting your off days, etc. I would say it all depends on your team. If you manage to get into a good team with a good leader, even if the work is tough, it's a lot more manageable.Cons: The pace is definitely fast, but a good team helps to make it better. My team works hard, but we also respect off days and weekends as much as we can.
- 4.0Overall acceptable, but expected poor WLBMachine Learning Engineer • Current EmployeeSingapore, SingaporeOctober 27, 2025Pros: quite a lot of challenges, and the colleagues are excellent.Cons: Need to work overtime very often and have meetings at night.
TikTok Interview Questions
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