Software Engineer In Machine Learning applicants have rated the interview process at LinkedIn 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 54% positive. This is according to Glassdoor user ratings.
Candidates applying for Software Engineer In Machine Learning roles take an average of 11 days to get hired, when considering 10 user submitted interviews for this role. To compare, the hiring process at LinkedIn overall takes an average of 28 days.
Common stages of the interview process at LinkedIn as a Software Engineer In Machine Learning according to 10 Glassdoor interviews include:
Phone interview: 59%
Presentation: 12%
Skills test: 12%
One on one interview: 12%
Group panel interview: 6%
Here are the most commonly searched roles for interview reports -
I applied through a recruiter. The process took 5 days. I interviewed at LinkedIn (Mountain View, CA) in Jul 2019
Interview
Phone interview: 1 coding questions followed by 1 machine learning related question
The interviewer started with a self introduction and ask me some behavior questions about what my daily routine is and why interested in working in linkedin.
Then we started the coding question using Skype pad for about 20 minutes. After I finished it, he asked me to do some unit testing to cover each edge case.
Then we went through the machine learning related questions for about 20 minutes.
Interview questions [2]
Question 1
Machine learning related question:
The company currently have: 1. user profiles 2. a list of job each user applied 3. job profiles
question: how to build a job recommendation system using these information?
Coding question:
Given a 2d grid map of '1's (land) and '0's (water), count the number of islands. An island is surrounded by water and is formed by connecting adjacent lands horizontally or vertically. You may assume all four edges of the grid are all surrounded by water
I applied online. I interviewed at LinkedIn in Jan 2021
Interview
Phone screen then onsite.
Phone screen: 1 coding question and 1 question regarding precision/recall.
Onsite (6 rounds): 2 coding, 1 product design, 1 ML theory, 1 lunch, 1 behavioral.
They asked a lot of questions in ML theory round.
Recruiter's feedback: 1. I could not answer "what is '1' in F1 measure?" 2. I just describe superficially. Actually, I started thorough descriptions at the very beginning but the interviewer stopped me.
Seemingly, the interviewers are biased toward people from Statistics or a certain country.
I applied through a recruiter. I interviewed at LinkedIn (Mountain View, CA)
Interview
Got opportunity via recruiter. There was a tech screen followed by Onsite.
Tech Screen included background questions, experience questions as well as coding on collabedit space.
The interviewer was helpful and gave prompts for answering the question.
Was expected to give executable code with no syntax errors.
Interview questions [1]
Question 1
write a function to sample from a multinomial distribution