This is a follow-up to my earlier post (LINK). I recently went through 7 interview rounds—2 phone screens and 5 onsite rounds—for an Applied Scientist 2 position.

The phone screens focused on machine learning (ML) fundamentals, statistics, probability, and a few basic data structures and algorithms (DSA) questions (though I don't recall the exact ones). The 5 onsite rounds were as follows:

1. ML Breadth Round: Covered a wide range of ML topics with a heavy emphasis on math.

2. ML Depth Round: A deep dive into the specifics of my resume and past projects.

3. Business Problem Round: I was asked to design Alexa from scratch—not the software system design, but the ML system design. This included identifying necessary datasets, tasks to be performed, model selection and justification, and evaluation metrics.

4. Behavioral Round (1.5 hours): A rigorous behavioral interview focused on leadership principles.

5. DSA Round: Two questions were asked—one similar to the course schedule problem, which required topological sorting, and the other was about finding the longest duplicate substring in a given string.

Although I wasn't offered the L5 (Applied Scientist 2) role due to my relatively limited industry experience, I did receive an L4 (Applied Scientist 1) offer, and it was at the top end of the L4 salary band. My next goal is to work hard and earn that L5 promotion next year.

For context, here's a snapshot of my LeetCode journey so far:

Hey everyone

After clearing the phone screen round, I got a call regarding the Applied Scientist virtual onsite round at Amazon.

It will probably be a 5 hour onsite (details are yet to be discussed with the recruiter). This sub has extensive information about the leetcode style questions but I wanted to ask the MLEs, Applied Scientist and Data Scientists on this sub as to what to expect in the ML depth and breadth round and Business application round. And how to prepare for each of these rounds? If you could share your some resources that would be helpful.

Also below are my leetcode stats, from here on I will focus mainly on Amazon but any other suggestions are appreciated.