Machine Learning Engineer Interview Experience - Singapore
January 13, 2026
Neutral ExperienceNo Offer
Process
I applied through a recruiter. The process took 2 weeks.
From what I know, there will be around 3-4 technical rounds. The last round will be with the head or director. There will be standard questions:
- Coding
- System
- Machine learning
- Predictive model
- Data processing
Questions
There was a question about the difference between XGBoost and Random Forest, and a LeetCode problem on the maximum subarray sum.
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Interview Statistics
The following metrics were computed from 24 interview experiences for the TikTok Machine Learning Engineer role in Singapore.
Success Rate
25%
Pass Rate
TikTok's interview process for their Machine Learning Engineer roles in Singapore is very selective, failing most engineers who go through it.
Experience Rating
Positive38%
Neutral33%
Negative29%
Candidates reported having mixed feelings for TikTok's Machine Learning Engineer interview process in Singapore.
TikTok Work Experiences
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.
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
Great Pay, Terrible Balance
Machine Learning Engineer • Current Employee
Singapore, Singapore
September 25, 2020
Pros: High salary for the employee
Cons: Bad work and life balance.
- 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.
- 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.
- 4.0Great Pay, Terrible BalanceMachine Learning Engineer • Current EmployeeSingapore, SingaporeSeptember 25, 2020Pros: High salary for the employeeCons: Bad work and life balance.
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