Machine Learning Engineer applicants have rated the interview process at Eneba with 4 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 80% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 30 days to get hired, when considering 1 user submitted interviews for this role. To compare, the hiring process at Eneba overall takes an average of 22 days.
Common stages of the interview process at Eneba as a Machine Learning Engineer according to 1 Glassdoor interviews include:
Phone interview: 33%
One on one interview: 33%
Skills test: 33%
Here are the most commonly searched roles for interview reports -
Recruiter interview->Technical interview
Very pleasant interview. Got feedback and the exact reasons why I was rejected. The technical questions were around the design of the system, and from the field I am most familiar with, even though that's not what the company was doing.
After being rejected got a folowup meet to get the feedback on why I was rejected and what the areas for improvement are, which was a first for me.
Interview questions [1]
Question 1
What loss did I use in my model?
How do I measure if the model is working well after deployment?
I applied through a recruiter. The process took 4 weeks. I interviewed at Eneba (Kaunas) in Nov 2024
Interview
Interview process was very smooth. It was pleasure to communicate with both: Talent Acquisition Partner and team members. Everyone seemed strong in both technical and human qualities. The experience was professional and engaging.
Interview questions [1]
Question 1
There were few questions about how I handled various situations in the past and what could be done differently. This shows team pays attention not only to technical knowledge, but also values positive attitude.