I applied through a recruiter. I interviewed at LinkedIn (Mountain View, CA) in Jan 2016
Interview
Phone screen interview was scheduled 3 times. The first 2 time interviewer just didn't call without any notice. For this interview you have to set a time aside since it needs to be done on a computer. So you will have to be out of office for the interview. That's why I was upset that the interview was cancelled twice without any notice.
There were 2 interviewers. One didn't speak English very well, so it was very difficult to understand. In fact I had to ask to repeat every time.
Interview questions [3]
Question 1
Following questions were asked:
1) What is a transaction?
3) For a given array find the maximum size palindrome subset. The subset may be not continues.
For input 1, 2, 4, 5, 1 the answer is 3, the subset is 1,2,1
Interviewed for an SDE role. The process was well-organized and the recruiters were responsive throughout. That said, the technical rounds were significantly more challenging than expected — definitely come prepared to go deep. Overall a valuable experience regardless of the outcome.
That was a real stroke of luck — when I got to the coding round and encountered a question on finding the maximum subarray sum, I had literally seen this exact problem on prachub.com a few days earlier. The interview kicked off with a recruiter screen, followed by a technical phone interview. It was intense, especially with the focus on algorithms and data structures. I also faced some behavioral questions that challenged my experience. After a final onsite round, I received an offer and happily accepted. Overall, it was tough but rewarding.
Interview questions [1]
Question 1
Given an integer array nums, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum. Walk through Kadane's algorithm and explain the O(n) approach.
Overall, a good interview process and the team were very friendly during the interview process and it was very good and pleasant. Nothing in regard to negative feedback or anything as such like that.
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