Machine Learning Engineer Interview Experience - London, United Kingdom
April 25, 2024
Neutral ExperienceNo Offer
Process
The interview process has at least three stages:
- A call with the hiring manager.
- A technical coding interview (HackerRank) combined with machine learning questions.
- A call with team members.
The second stage is very impersonal. The interviewer does not turn their camera on at all, and you can frequently hear them talking to other people in the background.
Questions
They asked about key ML architectures like ResNets and Transformers.
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Interview Statistics
The following metrics were computed from 7 interview experiences for the TikTok Machine Learning Engineer role in London, United Kingdom.
Success Rate
0%
Pass Rate
TikTok's interview process for their Machine Learning Engineer roles in London, the United Kingdom is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive14%
Neutral43%
Negative43%
Candidates reported having very negative feelings for TikTok's Machine Learning Engineer interview process in London, United Kingdom.
TikTok Work Experiences
5.0
Highly depends on the team
Machine Learning Engineer • Current Employee
July 15, 2025
Pros: High salary and good benefits
Cons: For different teams, the culture and work-life balance can be totally different.
4.0
Hate the 4 days RTO. Others are okay
Machine Learning Engineer • Current Employee
Sydney, New South Wales, Australia
June 27, 2025
Pros: intelligent fellows, so that everything works smoothly.
Cons: Have to be 4 days RTO.
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.
- 5.0Highly depends on the teamMachine Learning Engineer • Current EmployeeJuly 15, 2025Pros: High salary and good benefitsCons: For different teams, the culture and work-life balance can be totally different.
- 4.0Hate the 4 days RTO. Others are okayMachine Learning Engineer • Current EmployeeSydney, New South Wales, AustraliaJune 27, 2025Pros: intelligent fellows, so that everything works smoothly.Cons: Have to be 4 days RTO.
- 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.
TikTok Interview Questions
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