I had the opportunity to participate in the Amazon ML Summer School after being selected through an application process. The selection involved an aptitude test and an OA (Online Assessment) test, which I successfully completed. During the summer school, I learned from Amazon scientists through various modules.
About a week after completing the summer school, I received an email inviting me for an interview. The interview process consisted of several rounds.
1st Round:
In the first round, I faced 2-3 DSA (Data Structures and Algorithms) problems of medium difficulty level in the OA. I managed to solve them correctly and qualified for the next round.
2nd Round:
The second round was a technical interview focused on DSA. I was asked three questions, including one on HashMap, another related to it, and a third one on graphs. I explained my approach, coded the solutions, and discussed them with the interviewers. After two days, I received an invitation for the next technical round.
3rd Round:
In the third round, the focus shifted to ML (Machine Learning). Despite having limited experience and no significant ML projects, I relied on my understanding of basic concepts during the interview. However, as the position primarily required ML expertise, I didn't advance to the HR round.
Overall, it was a valuable experience. My advice for future applicants is to focus on preparing well for DSA and having substantial ML projects, as concepts alone might not suffice.