Machine Learning Engineer applicants have rated the interview process at Wayfair with 3.5 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 57% positive. To compare, the company-average is 51.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 16 days to get hired, when considering 7 user submitted interviews for this role. To compare, the hiring process at Wayfair overall takes an average of 22 days.
Common stages of the interview process at Wayfair as a Machine Learning Engineer according to 7 Glassdoor interviews include:
Phone interview: 31%
Presentation: 23%
Group panel interview: 15%
One on one interview: 15%
Skills test: 15%
Here are the most commonly searched roles for interview reports -
I applied online. I interviewed at Wayfair (New York, NY) in Nov 2020
Interview
One test and one video interview. The test had programming questions as well as some MCQs. They were all data science related and coding was in python. Didn’t hear back after the first round video interview which happened in November 2020, ghosted by the company!
I applied online. I interviewed at Wayfair (Boston, MA)
Interview
It was mix of conversational and code writing process for the interview. Recruiter sent me some materials to prepare for the case based ML interview. For this role they set 6-7 rounds of interview
I applied through a recruiter. The process took 1+ week. I interviewed at Wayfair (New York, NY) in Jan 2022
Interview
Recruiter reached out on LinkedIn.
Screening round: all behavior type questions with the team director.
I thought it went great, but may be they were looking for someone different. They sent reject.
I applied online. The process took 3 weeks. I interviewed at Wayfair in Jan 2022
Interview
The process was fairly straightforward. Started by talking to a recruiter about my background and interests. Met with the hiring manager going into more detail on resume and background. Finally ended with a virtual onsite panel with 4 interviews with each around 45 min.
Started with a coding type problem, and other ML concepts, followed by a system design. The last 2 sessions covered behavioral and product sense.