Electronic Arts Machine Learning Engineer interview questions
Updated Feb 23, 2026
based on 3 ratings
Difficulty
Average
Experience
Mostly negative
How others got an interview
100%
Applied online
Applied online
Interview search
3 interviews
Electronic Arts interviews FAQs
Machine Learning Engineer applicants have rated the interview process at Electronic Arts with 2.7 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 33% positive. To compare, the company-average is 56.9% positive. This is according to Glassdoor user ratings.
Common stages of the interview process at Electronic Arts as a Machine Learning Engineer according to 3 Glassdoor interviews include:
Phone interview: 50%
Skills test: 50%
Here are the most commonly searched roles for interview reports -
The interview process consisted of two stages. The first was a conversation with the hiring manager to assess overall fit, followed by a technical interview in the second stage. The process was straightforward, and overall, I had a very positive experience. The questions were primarily focused on my past projects and hands-on experience.
Interview questions [1]
Question 1
Have you ever encountered a challenging problem, and how did you approach and resolve it?
I applied online. I interviewed at Electronic Arts (Vancouver, BC)
Interview
The company's recruiter called me, and everything went well. They mentioned I would be moving on to the next step with the hiring manager. However, even after following up, I never heard back from them. It is more respectful of people's time to at least let them know if they’ve been rejected or if plans have changed, rather than simply disappearing.
I applied online. I interviewed at Electronic Arts (Edmonton, AB)
Interview
The first step is a phone call from HR. The second step was with the experienced ML team member. EA team was more interested in large-scale platform experience. This round is about the experience and personal background.
Interview questions [1]
Question 1
More related to large-scale ML platform for the internal usage.