Process
I applied online.
Recruiter call, then 2 rounds of interviews. Each round has 2 interviews:
- 1st round asked about background/resume, and has a coding session (LeetCode style and SQL).
- 2nd round is behavioral questions and general knowledge questions.
Questions
Write a SQL to find the person with the second highest salary, without using subquery
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Interview Statistics
The following metrics were computed from 55 interview experiences for the Apple Machine Learning Engineer role.
Success Rate
22%
Pass Rate
Apple's interview process for their Machine Learning Engineer roles is very selective, failing most engineers who go through it.
Experience Rating
Positive51%
Neutral40%
Negative9%
Candidates reported having very good feelings for Apple's Machine Learning Engineer interview process.
Apple Work Experiences
4.0
Machine Learning Engineer
Machine Learning Engineer • Current Employee
New York, New York, United States
January 27, 2021
Pros: That's a very great company, and if you have skills, try your chance.
Cons: There are no cons with this great company. I still love it.
5.0
Impactful place to work
Machine Learning Engineer • Current Employee
Cupertino, California, United States
February 22, 2020
Pros: Your work is deployed worldwide, and it can happen faster than you think. Being detail-oriented is crucial to your performance and happiness here.
Cons: The culture varies significantly among teams. Some teams support employees beautifully, while others do not.
5.0
Great Job, Great Benefits
Machine Learning Engineer • Current Employee
Cupertino, California, United States
July 20, 2022
Pros: Great, good job, great benefits.
Cons: Nothing terrible to say about it.
- 4.0Machine Learning EngineerMachine Learning Engineer • Current EmployeeNew York, New York, United StatesJanuary 27, 2021Pros: That's a very great company, and if you have skills, try your chance.Cons: There are no cons with this great company. I still love it.
- 5.0Impactful place to workMachine Learning Engineer • Current EmployeeCupertino, California, United StatesFebruary 22, 2020Pros: Your work is deployed worldwide, and it can happen faster than you think. Being detail-oriented is crucial to your performance and happiness here.Cons: The culture varies significantly among teams. Some teams support employees beautifully, while others do not.
- 5.0Great Job, Great BenefitsMachine Learning Engineer • Current EmployeeCupertino, California, United StatesJuly 20, 2022Pros: Great, good job, great benefits.Cons: Nothing terrible to say about it.
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