Machine Learning Engineer Intern applicants have rated the interview process at Adobe with 3.1 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 50% positive. To compare, the company-average is 59.9% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer Intern roles take an average of 41 days to get hired, when considering 8 user submitted interviews for this role. To compare, the hiring process at Adobe overall takes an average of 31 days.
Common stages of the interview process at Adobe as a Machine Learning Engineer Intern according to 8 Glassdoor interviews include:
One on one interview: 43%
Skills test: 29%
Presentation: 14%
Other: 14%
Here are the most commonly searched roles for interview reports -
Start with introduction, and then talked about previous work done. The interviewer would then ask follow-up questions during the walkthrough. Afterward there is the regular Q&A procedure. Overall smooth and interactive.
Interview questions [1]
Question 1
In a classification problem, if the classes are biased, what should you do?
I applied online. The process took 1 week. I interviewed at Adobe in Oct 2023
Interview
There were two people, but only one was asking the questions. First, he asked me about my research and projects. He asked some follow-up questions on the projects. Then it was like a rapid-fire round with questions on ML like working of the ML pipeline, layers inside a CNN, evaluation metrics, etc.
Interview questions [1]
Question 1
What evaluation metric do you use if both False positive and False negative should be considered?
After resume screening, the HR contact me to schedule interview. There are two rounds of interview. First one was about coding and ML basics; second was asking detail questions about ML projects on the resume and follow a ML case study
Interview questions [1]
Question 1
Machine learning questions about binary classification