Process
Basically, MLE rounds for Apple go like this, at least for entry-level positions like this one:
- Hiring manager round
- Technical screen, which involves coding
- Virtual loop interviews
Be prepared to talk about your recent experiences in good detail.
Questions
Resume and recent project-based questions - hiring manager round
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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
5.0
Good Support, Team Changes
Machine Learning Engineer • Current Employee
Cambridge, England, United Kingdom
May 21, 2022
Pros: Good support and good impact.
Cons: Restructuring of teams is inevitable, changing the directions of teams.
5.0
General Apple review
Machine Learning Engineer • Current Employee
Cupertino, California, United States
August 26, 2025
Pros: - Teammates from whom you can learn
- Job stability
- Good benefits
Cons: - Low visibility across organizations.
4.0
One of the best companies to work for
Machine Learning Engineer • Current Employee
San Jose, California, United States
September 17, 2022
Pros: - Product focus
- Performance driven
- Excellent cross-collaboration
- Result-oriented
Cons: - Can cause burnout.
- Redundant work effort in some parts of the organization.
- Some may find it not people-oriented due to its performance focus.
- 5.0Good Support, Team ChangesMachine Learning Engineer • Current EmployeeCambridge, England, United KingdomMay 21, 2022Pros: Good support and good impact.Cons: Restructuring of teams is inevitable, changing the directions of teams.
- 5.0General Apple reviewMachine Learning Engineer • Current EmployeeCupertino, California, United StatesAugust 26, 2025Pros: - Teammates from whom you can learn - Job stability - Good benefitsCons: - Low visibility across organizations.
- 4.0One of the best companies to work forMachine Learning Engineer • Current EmployeeSan Jose, California, United StatesSeptember 17, 2022Pros: - Product focus - Performance driven - Excellent cross-collaboration - Result-orientedCons: - Can cause burnout. - Redundant work effort in some parts of the organization. - Some may find it not people-oriented due to its performance focus.
Apple Interview Questions
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