Process
The phone screen was more in-depth than I anticipated, starting with a few behavioral questions before moving into technical territory.
I was asked about implementing k-means clustering and had to explain its convergence—definitely a challenge.
The real kicker was when I recognized a coding problem about finding the median of two sorted arrays; I had just practiced that on prachub.com a couple of days earlier.
After the technical rounds, which included designing a recommendation system for Apple Music, I received an offer, and I accepted it.
Questions
Implement k-means clustering from scratch and explain convergence.
Design a personalized recommendation system for Apple Music.
Find the median of two sorted arrays in log time.
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Interview Statistics
The following metrics were computed from 55 interview experiences for the Apple Machine Learning Engineer role.
Success Rate
Apple's interview process for their Machine Learning Engineer roles is very selective, failing most engineers who go through it.
Experience Rating
Candidates reported having very good feelings for Apple's Machine Learning Engineer interview process.
Apple Work Experiences
- 4.0Stable Pay, Limited GrowthMachine Learning Engineer • Current EmployeeSan Diego, California, United StatesApril 21, 2025Pros: Easy work, relatively high and stable pay, not a risk of layoff.Cons: There is not much room for growth at Apple. They care too much about visibility, DEI, and...
- 5.0Interesting R&d, Sometimes DifficultMachine Learning Engineer • Former EmployeeSan Jose, California, United StatesOctober 19, 2020Pros: New interesting R&D projectsCons: At some times, work becomes difficult.
- 5.0Difficult to get in, very interesting projectsMachine Learning Engineer • Current EmployeeZürich, SwitzerlandNovember 12, 2024Pros: - Great salary - Good work-life balance - Nice benefitsCons: - Late evening meetings - No cafeteria
Apple Interview Questions
