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Jupiter Money Interview Experience for ML Engineer (Off-Campus)

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  • Last Updated : 19 Apr, 2022
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 There were in total of 3 rounds – The coding/Problem-solving round, Technical Interview, and Hiring Manager Round.

Round 1 – Coding/Problem-Solving round (90 minutes): This round comprised of 2 GFG hard/expert level graph questions, 13 technical MCQs, and 2 optional behavioral questions. This round happened on the CoderByte platform.

  • One problem was a variation of finding the longest path from one node to another in a graph (finding the diameter of a graph).
  • The second problem was a variation of topological sorting.

I managed to solve both questions successfully. Aid to search for code syntax and common algorithms were inbuilt into the CoderByte platform.

Round 2 – Technical Interview (Online – 75 minutes): After completing the first round I got a call from the recruiter informing my selection for the second round on the same day. The second round happened after 3 days.

The interviewer was very friendly and started the interview with his introduction. This round also happened on the CoderByte platform. He then asked me to introduce myself. After that, he jumped straight to the questions. He started by asking me to explain my summer internship project (deep learning) with all the details and my role in it since it was a team project. This felt more like a discussion since he seemed too interested in the project. After this, he jumped straight to DSA questions. The questions were very simple (GFG easy/medium). He asked 4 questions in total.

  • Wave Sort an array. I first gave him the sorting and swapping alternate elements approach. But, he asked me to optimize it and code it as well. O(N) solution was accepted finally. 
  • Suppose you are given a resume, you need to find the most frequently occurring word in it. Since this was an open-ended question I clarified how will the resume be provided (in .pdf or .txt format) which he clarified to be .txt format. I gave him the approach of maintaining a hash map of all the words and their frequencies. He told me to generalize this tool for any .txt file. I told him that there will be hash collisions for large files. He asked me about hash collision mitigating techniques. I explained to him about Open addressing, Chaining, etc. He asked me about asynchronous code and parallel programming techniques as well.
  • Write an SQL query to find the Nth highest salary of an employee from the salary table.
  • Peak finding variation (Binary Search). He asked me to code the solution.

This round ended with him asking me if I had any questions for him and a general discussion.

Round 3 – Hiring Manager round (Online – 35 minutes): I got a call after 4 days to schedule this round. This was a short round with the Data Science project team manager.

  • He started with my introduction and then followed up with his own. He asked me about the previous rounds and my interview experience up till now.
  • He then moved on to my project (Machine Learning) and asked me to describe the experience of building one as well as its features. He asked a few follow-up questions on the choice of the tech.
  • He also asked me a few questions about Operating systems like paging and memory management.
  • Also, he asked me to explain what happens when you hit a URL. He expected an explanation of the entire flow of the request in the network OSI model.
  • Finally, he asked a few generic questions like where do you see yourself in 2-3 years and what are your expectations, etc.

He asked me if I had any questions. I asked a few questions about the role and the expectations. The interview concluded after that.

Final Verdict: Selected!


  • 1) Be confident with your projects. Know the ins and outs of them.
  • 2) Clarify what you do not understand until you and the interviewer agreed.
  • 3) It’s okay to not know a few things.
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