Unify

Role: SDE(ML)

College: Not Specified

Interview Date: Not Specified (Posted July 23, 2025)

Interview Type: Off-Campus

Result: Selected

Difficulty: Medium

Rounds: 3 rounds

Topics Asked: Data Structures, Algorithms, Project, Thesis, Machine Learning Basics

Experience:

The candidate applied for an SDE(ML) position through a recruiter. The interview process consisted of three rounds.

Round 1: Coding Question + Project
This round involved a coding question, which was a variation of finding the valley point. Additionally, there was a discussion about the candidate's projects and thesis.

Round 2: Coding Question + Machine Learning Basics
The second round also featured a coding question, which was to find all permutations of a given string. This was followed by questions on Machine Learning Basics, including:

• Difference between Classification and Regression.
• What is an F1 score? How would you use it?
• How to Tackle Overfitting and Underfitting?
• How to Handle Outlier Values?
• How do you make sure which Machine Learning Algorithm to use?
• What is Ensemble learning?
• What is the P-value?
• What are Parametric and Non-Parametric Models?
• Explain Correlation and Covariance.

Round 3: Managerial Round
This was the final managerial round.

A day after the managerial round, the candidate received a call from HR, and the offer letter was shared on the same day. The tip provided was to be strong in basic ML mathematics.