Process
Virtual Onsite Interview:
- 5 rounds of coding/Machine Learning questions
Presentation:
The presentation is about my research. It's a 45-minute presentation. People in the team will ask some questions about your research.
Questions
The interview consisted of:
- Two rounds with Leetcode questions.
- Three rounds with ML/NLP-related questions.
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Interview Statistics
The following metrics were computed from 36 interview experiences for the Apple Machine Learning Engineer role in United States.
Success Rate
11%
Pass Rate
Apple's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive44%
Neutral50%
Negative6%
Candidates reported having very good feelings for Apple's Machine Learning Engineer interview process in United States.
Apple Work Experiences
4.0
Stable company, slow advancement
Machine Learning Engineer • Former Employee
Cupertino, California, United States
March 16, 2025
Pros: Strong talent and product ecosystem. Technical middle management. Legitimate focus on user privacy internally. Great office & environment design.
Cons: Depending on the team, there may be middling product vision and infra. Promotions and pay come slowly. You need to really advocate for yourself, else no one will. Teams often work on secretive & siloed projects; communication can feel tough. Upper management makes the company feel very corporate and boomer.
5.0
Good place to work
Machine Learning Engineer • Former Employee
Zürich, Switzerland
December 14, 2019
Pros: Put in good conditions to work, smart people, interesting projects.
Cons: Can end up not making big decisions and more just implementing.
4.0
Great Learning, Sucky Commute
Machine Learning Engineer • Current Employee
July 14, 2022
Pros: The job is great, work-life balance is great, and I'm learning a lot.
Cons: No free stuff, commute sucks.
- 4.0Stable company, slow advancementMachine Learning Engineer • Former EmployeeCupertino, California, United StatesMarch 16, 2025Pros: Strong talent and product ecosystem. Technical middle management. Legitimate focus on user privacy internally. Great office & environment design.Cons: Depending on the team, there may be middling product vision and infra. Promotions and pay come slowly. You need to really advocate for yourself, else no one will. Teams often work on secretive & siloed projects; communication can feel tough. Upper management makes the company feel very corporate and boomer.
- 5.0Good place to workMachine Learning Engineer • Former EmployeeZürich, SwitzerlandDecember 14, 2019Pros: Put in good conditions to work, smart people, interesting projects.Cons: Can end up not making big decisions and more just implementing.
- 4.0Great Learning, Sucky CommuteMachine Learning Engineer • Current EmployeeJuly 14, 2022Pros: The job is great, work-life balance is great, and I'm learning a lot.Cons: No free stuff, commute sucks.
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