multiple interviews starting with HR, ML knowledge and coding tasks ranging from small questions to big and deeper ones and trying to see how you can discuss ML problems and analyse them
Interview questions [1]
Question 1
What is the most difficulty you have during your career?
I applied online. The process took 4 weeks. I interviewed at Snap (London, England) in Sep 2025
Interview
The discussions on Deep Generative AI and the technical nuances of the topics were very engaging. The coding problems were challenging and thought-provoking. Also, the conversation on the ML Systems Designing in production stage was particularly insightful for real-world applications.
Interview questions [1]
Question 1
How to use multiple GPU training and describe optimisation techniques for DL inference?
Nice, kind interviewer.
An interviewer ask me a couple of questions. Then we have a code interview.
They asked to write a code, ask a few questions based on a result, ask me to fix my bugs
The process was fairly standard and acceptable, neither outstanding nor disappointing. It met expectations but lacked any exceptional aspects. Overall, it was an average experience with more room for improvement....
ML Engineer applicants have rated the interview process at Snap with 3.5 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 50% positive. To compare, the company-average is 46.1% positive. This is according to Glassdoor user ratings.
Candidates applying for ML Engineer roles take an average of 30 days to get hired, when considering 4 user submitted interviews for this role. To compare, the hiring process at Snap overall takes an average of 26 days.
Common stages of the interview process at Snap as a ML Engineer according to 4 Glassdoor interviews include:
One on one interview: 40%
Phone interview: 20%
Skills test: 20%
Group panel interview: 10%
Personality test: 10%
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