Machine Learning Engineer applicants have rated the interview process at X with 2.9 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 39.4% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 21 days to get hired, when considering 10 user submitted interviews for this role. To compare, the hiring process at X overall takes an average of 29 days.
Common stages of the interview process at X as a Machine Learning Engineer according to 10 Glassdoor interviews include:
One on one interview: 27%
Presentation: 20%
Phone interview: 20%
Group panel interview: 13%
Other: 7%
Skills test: 7%
Background check: 7%
Here are the most commonly searched roles for interview reports -
Phone screen at Twitter for MLE II. One hour coding interview with a software engineer on the same team. Spent the first 10 minutes going through the resume and the rest 45 minutes doing leetcode questions.
Interview questions [1]
Question 1
Leetcode question with minor change. Apply DFS/BFS to traverse a matrix. Follow-up question is another leetcode question that requires knowledge of prefix tree.
I applied online. The process took 3 weeks. I interviewed at X (San Francisco, CA) in Sep 2024
Interview
Not complicated, multi layered / multi round, many questions asked about prior work history in machine learning, were looking for young, hungry, experienced candidates. Easy for them to find and sift through since they're a premier place to work at for this application.
Interview questions [1]
Question 1
Asked if I was willing to work at the office at all times, essentially live there, come to find out they're moving to TX and thus I can't follow them.
The interviewer gave me a coding question and ask me to solve it. I told him my idea first and then start writing code. After I finish the basic solution, he asked me to optimize it. Then he asked me about time and space complexity.