Google Machine Learning Engineer interview questions
based on 43 ratings - Updated May 26, 2026
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42%
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4%
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Machine Learning Engineer applicants have rated the interview process at Google with 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 71.6% positive. This is according to Glassdoor user ratings.
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I interviewed for a Google ML Engineer role. The process included coding challenges, ML system design, and behavioral rounds. Emphasis was on problem-solving, scalability, and domain knowledge. Preparation involved LeetCode, ML fundamentals, and practice mock interviews. Insightful experience overall!
Two online coding questions on their interface. One was an easy question focussed on just the brute force method, and the other was a leetcode hard question aimed at the performance of the code.
Interview questions [1]
Question 1
Minimum Number of Increments on Subarrays to Form a Target Array
It was good , they asked some level of Machine learning questions but at the end in the Interview, they asked all about pytorch . It was amazing. The experience was amazing and it was really good.