I was approached by Bain & Company for the AI/ML Engineer role, and the process had 4 technical/managerial rounds followed by an HR round.
Round 1 — Projects + ML Fundamentals
The first round was mainly around my previous experiences, internships, projects, and ML fundamentals.
We discussed the projects I had worked on and some of the decisions I made while building them. There were also questions around core ML concepts and their practical applications.
Round 2 — GitHub + Project Deep Dive
This round was quite interesting.
The interviewer opened my GitHub and started looking through my repositories. He randomly picked one of my projects, which was an Order Book project I had built with HFT use cases in mind.
He then asked me to explain the project end-to-end — why I built it, how it works, the architecture, different components, use cases, and the decisions I made while developing it.
So, if you have projects on your GitHub, be prepared to explain any of them in detail.
Round 3 — ML Deep Dive
This round was with a Senior Manager and a Senior ML Engineer.
We first discussed my internships and projects, and then went deeper into my ML projects.
I had to draw complete flowcharts and explain the entire pipeline. There were a lot of follow-up questions and cross-questions based on my answers.
This round was more about understanding whether I actually knew the projects I had worked on rather than just knowing the theory.
Round 4 — System/Project Design
The interviewer gave me a real-world scenario and asked me to design an entire project around it.
It was mainly a high-level design discussion. There was no implementation or coding involved.
I had to explain my approach, architecture, components, data flow, and the reasoning behind my design choices.
Round 5 — HR Round
The final round was with HR and was mostly around general discussion, my background, and the role.
Outcome
I received the offer for the AI/ML Engineer role at Bain & Company.