I applied through an employee referral. I interviewed at Amazon (San Francisco, CA) in Feb 2021
Interview
I went through two Interview steps. The first one covered the machine learning fundamentals and the second part went through algorithm design.
The machine learning part was interesting and efficient and was moderate level.
The algorithm design part on the other hand was not organized. The interviewer asked me to think loud but kept interrupting and somehow misguiding me. I think the problem was that I was coding in Python while the interviewer seemed to come from a C++ background. So, he did not really get what I meant by some data structures, etc.
Interview questions [1]
Question 1
What is the difference between bagging and boosting?
There are three rounds in total. The process begins with a coding round, followed by the main interview loop, where you will meet the team and discuss technical skills, experience, and fit.
First round is fun, second round, which is also the final round involved 5 sessions, with different focus. For some sessions, not be able to present my story completely, time was tight, and interviewers were rushing.
4 rounds:
ML breadth + Depth: Conceptual knowledge about ML and work experience discussion
Problem solving: Leetcode (Medium) + Basic ML concepts
Design + LP round: Use case discussion + Behavioural questions
Bar Raiser - LP round: Behavioural questions - Interviewer was non technical
1
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