Candidates applying for Machine Learning Engineer roles take an average of 17 days to get hired, when considering 5 user submitted interviews for this role. To compare, the hiring process at Yelp overall takes an average of 18 days.
Common stages of the interview process at Yelp as a Machine Learning Engineer according to 5 Glassdoor interviews include:
Phone interview: 40%
Skills test: 40%
Background check: 20%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 2 weeks. I interviewed at Yelp (Cairo, Cairo Governorate) in Oct 2020
Interview
Pre-Interview then Technical one (that's how far i got) where we discussed my exp then was asked couple of statistics questions and to implement solutions (i picked python back then)
Other Machine Learning Engineer Interview Reviews for Yelp
The application process took quite a long time. The interviewer was friendly and nice. The questions asked were all technical and entry-level, so be well prepared, and you will be fine.
There are five rounds of interviews. The first is a 30-minute HR screening, followed by a 1-hour live coding interview at a LeetCode medium level. The third round is a 15-minute cultural interview (optional). The fourth round is a 2-hour session that includes live coding, planning, and HR discussions.
I applied through an employee referral. The process took 6 weeks. I interviewed at Yelp (Toronto, ON) in Apr 2025
Interview
1 online coding screening and 2 rounds. First round a coding interview with a member of the Engineering team, and second round an onsite interview, with 4 interviews of system design, coding, behavioural, and "past projects". Overall the interviews were good, but after the last one, I didn't hear anything back for 2 weeks and then a rejection. When I asked for clarification, they emailed backed 3 weeks later saying "you didn't ask enough questions on the system design interview" which is their usual response, and not true in my case.
Interview questions [1]
Question 1
A lot of NLP basics in the coding interviews, like separating bi-grams and tokenizing a text using specific requirements.