Interviewed with a senior analytics manager for a data scientist role at Amazon. Interview was a 1 hour phone interview with a 15 minute SQL test to do on the spot. Interview questions were typical questions about CV and competency based questions according to their leadership principles which went really well and the interviewer kept repeating 'excellent' but the 15 min SQL test didn't go well- despite straightforward questions, I've never understood the point in testing coding skills in a time limit. Received an automated email a couple hours later that I was not successful in moving to the final round and that it was against their policy to provide feedback.
I guess its true what they say about Amazon- 0 consideration for applicants or employees. You spend an hour of your time interviewing and do a coding test to not receive any feedback.- v disappointing.
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.