Machine Learning Intern applicants have rated the interview process at TikTok with 3.8 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 19% positive. To compare, the company-average is 37.3% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Intern roles take an average of 13 days to get hired, when considering 16 user submitted interviews for this role. To compare, the hiring process at TikTok overall takes an average of 30 days.
Common stages of the interview process at TikTok as a Machine Learning Intern according to 16 Glassdoor interviews include:
Skills test: 36%
One on one interview: 25%
Background check: 14%
Phone interview: 11%
Other: 7%
IQ intelligence test: 4%
Presentation: 4%
Here are the most commonly searched roles for interview reports -
I applied through a recruiter. I interviewed at TikTok (San Jose, CA) in Feb 2026
Interview
The interview was 45 mins. The interviewer was friendly and responsive. It started with 15 mins introducing yourself with backgrounds and experiences. Then it's 20 mins live coding (one leetcode question). And final 10 mins open-ended question.
Interview questions [1]
Question 1
What is some classical recommendation system architectures?
I applied online. The process took 3 weeks. I interviewed at TikTok (Singapore) in May 2025
Interview
2 round technical, 1 round conversational, 1 round talk with HR. Technical interview revolves around statistical language modelling coding, LLM fine tuning knowledge and SQL. Not difficult but need wide range of knowledge
Interview questions [1]
Question 1
What methods are used to increase token throughput of LLM inference without sacrificing ability?
I applied through a recruiter. I interviewed at TikTok (San Jose, CA) in May 2025
Interview
They began with questions based on my resume, asking about my projects and their impact. Then we moved on to a couple of easy algorithm problems—binary search and a combinations question you can find on LeetCode. Finally, given my background, they asked a few machine learning questions focused on recent work