Looking back, I feel satisfied with how everything turned out, even though I declined the offer. Initially, I had a technical phone screen where they challenged me with a regression model critique and a subset sum problem. The DSA round went smoothly; funny enough, I had just tackled a similar problem on PracHub during my prep. Finally, I walked through a PDF evaluation codebase, which felt familiar as I’d reviewed that type of architecture breakdown beforehand. Overall, it was a comfortable process and a great learning experience.
I applied online. I interviewed at Apple (Austin, TX) in Mar 2026
Interview
It was a 5 rounds of the interview. Interviewers were very polite and helpful. The questions were not too tricky. Leetcode part was easier than I thought. Focused more on basics.
An HR reached out and scheduled a BQ round immediately, talked to the hiring manager and focused on my resume in detail, then after that leetcode round and ml round
Machine Learning Engineer applicants have rated the interview process at Apple with 3.2 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 55% positive. To compare, the company-average is 64% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 43 days to get hired, when considering 40 user submitted interviews for this role. To compare, the hiring process at Apple overall takes an average of 29 days.
Common stages of the interview process at Apple as a Machine Learning Engineer according to 40 Glassdoor interviews include:
Phone interview: 25%
One on one interview: 23%
Skills test: 22%
Personality test: 10%
Background check: 7%
Presentation: 7%
Group panel interview: 3%
IQ intelligence test: 2%
Other: 2%
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