I applied through an employee referral. I interviewed at Amazon in Oct 2020
Interview
The first round was a phone screening. I was asked about my work experience and a coding question on count of frequent words in a stream of text.
The virtual onsite interview had 6 rounds of 1 hour interviews.
Round1: Leadership principles and then a coding session. The question was to get the count of rows based on a criteria.
Round 2: Technical presentation on a project you did in the past
Round3: Leadership questions and questions on data science scenarios. Try to ask as many as questions you can.
Round 4: Leadership questions and basic machine learning concepts like difference between bagging and boosting, What is naive bayes, explain p-value in layman terms, what is a normal distribution.
Round 5: LP questions and very simple sql queries
Round 6: Completely leadership questions
Interview questions [1]
Question 1
What is difference between bagging and boosting
What is naive bayes algorithm
Explain p-value
Explain Bayes theorem
Explain bias variance tradeoff
Example of a high bias and high variance models
Looking back, I'm relieved I declined the offer, despite the intense experience. The interview process felt overwhelming, starting with some tough core ML concepts before diving into the LLM fundamentals. During the technical round, I recognized a tokenization question from a PracHub session I had done just a week before. It felt like a small win in an otherwise challenging interview. Ultimately, the pressure and expectations were high, but I felt it wasn't the right fit for me.
Interview questions [2]
Question 1
LLM fundamentals: tokenization design and KL-regularized SFT
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.