Phase 1: Elimination Round
The ML Craft, First Round had two segments:
Phase 2:
Two 60-minute coding rounds and an ML system Design Round:
In the first half of the interview, we discussed the challenges I faced while building my project and how I handled them. Basic questions from my project were asked.
In the second half of the interview, I was asked to design a recommendation system for Confluence to recommend articles.
NOTE: They stated that system design questions are based on the resume or previous experience. However, I had not previously worked on a recommendation system. This question might have been based on the team's requirements. The interviewer mentioned his experience working on recommendations and that it is his field of expertise.
Data Structures Round: They asked a variation of the "stock price fluctuation" problem from LeetCode. The focus was on the chosen data structure, its trade-offs, and time complexity. The code needed to be executable with unit tests within 60 minutes. A Java Developer interviewed me, and I completed my solution in Python. The interviewer provided hints throughout the interview, making it feel like a brainstorming session. The difficulty of the MLE interview is considered equal to that of an SDE role.
Code Design Round: The question was similar to the following:
Let's pretend we are in charge of a cinema. We want to figure out whether a new movie can be added to the existing schedule without removing any of the current movies.
Note that:
The following metrics were computed from 1 interview experience for the Atlassian Machine Learning Engineer II role in India.
Atlassian's interview process for their Machine Learning Engineer II roles in India is extremely selective, failing the vast majority of engineers.
Candidates reported having mixed feelings for Atlassian's Machine Learning Engineer II interview process in India.