Machine Learning Intern applicants have rated the interview process at Apple with 3.3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 73% positive. To compare, the company-average is 63.9% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Intern roles take an average of 19 days to get hired, when considering 11 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 Intern according to 11 Glassdoor interviews include:
One on one interview: 42%
Phone interview: 25%
Presentation: 17%
Skills test: 17%
Here are the most commonly searched roles for interview reports -
1st round: 30 min Zoom interview asking me about my research and interests. 2nd round: 1 hour seminar + 4 1h interviews with a coding (leetcode medium), technical ML questions, and more about my research.
Interview questions [1]
Question 1
What is linear regression, how to solve for linear regression etc.
I applied online. The process took 4 weeks. I interviewed at Apple (Prague) in Jan 2023
Interview
We went straight for a technical interview with the team lead. He was excellent and well-read on my background. Asked me relevant questions and respected my time. I didn't have enough knowledge on DSP therefore I did not get an offer, however the interview was great fun.
Interview questions [1]
Question 1
Was asked a lot of questions about my projects, machine learning, deep learning, statistics, time series analysis and digital signal processing.
I applied online. I interviewed at Apple in Feb 2023
Interview
Two rounds - Coding and technical interview. Coding round was easy. Technical interview was pretty demanding with super difficult questions based on NLP research. I interviewed for Machine Learning Research Intern Role and the team was working with NLP and Speech Processing.
Interview questions [1]
Question 1
Coding - Recursion and Array Manipulation Technical - BERT, Deep Learning Fundamentals and NLP research