Machine Learning Engineer applicants have rated the interview process at Stripe with 3.6 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 22% positive. To compare, the company-average is 45.8% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 17 days to get hired, when considering 9 user submitted interviews for this role. To compare, the hiring process at Stripe overall takes an average of 26 days.
Common stages of the interview process at Stripe as a Machine Learning Engineer according to 9 Glassdoor interviews include:
Phone interview: 44%
One on one interview: 44%
Skills test: 11%
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I applied online. The process took 3 weeks. I interviewed at Stripe
Interview
Talked with recruiter about job responsibilities and job duties.
After about a week got to a phone screen with the hiring manager.
Mostly behavioral questions but I could see that despite my answers they kept looking displeased and back at my resume. I read a bit between the lines here…
First time in my life I’ve been discriminated against because of my age!
Don’t bother applying here if you are not in your 20’s. Just sad.
I applied through an employee referral. I interviewed at Stripe (San Francisco, CA) in Jun 2026
Interview
Pre-onsite step has two rounds. One is ML integration round. You need to work with a pre-loaded dataset, process the data and train a model. Another one is a programming problem with a few tasks. 2hrs in total.
Interview questions [1]
Question 1
Process the data and train a predictive model for the target. What is data normalization used for?
Online Assessment — The first round of interviews is scheduled to include both coding and machine learning problems. Overall, the process appears to follow a fairly standard interview procedure, beginning with technical assessment before moving into later-stage evaluations.
I applied through a recruiter. I interviewed at Stripe in Apr 2025
Interview
2 technical screens (coding, ml coding), onsite was 4 rounds (coding, debugging, system design, hiring manager). Coding questions were OOP and class oriented. Problems were practical, the ml coding round had a dataset provided and you had to build and evaluate a model in 1h.
Interview questions [1]
Question 1
system design had an emphasis on real time deployment