I applied through a recruiter. The process took 2 weeks. I interviewed at KnowDis Data Science (Calcutta) in Apr 2025
Interview
There were 3 Technical Rounds, 1st was one Python and 2nd and 3rd are complete depth of Deep Learning.
Python round covered coding K-Mean algorithm from scratch and a Leetcode medium level question on DFS.
Second round they asked questions around RNN, LSTM, Neural Network Initialization and Optimization
Second round they covered BERT my project in depth
Interview questions [4]
Question 1
Code K-Mean algorithm. They gave dummy data of 5 points, and two centers. I had to code and provide the output cluster centers.
Issues of RNN?
How can you solve them without moving to LSTM?
Gates of LSTM?
All the components of Transformer? What is the use of positional embedding? What is Multi-head attention? etc.
Different type of NN initializers, why they work?
Best optimizer? How they work?
All the components of Transformer? How are they trained
What is encoder vs decoder architecture?
What is masked decoder?
What is auto regressive LLMs?
What is the architecture of Distill BERT?
I applied online. The process took 2 weeks. I interviewed at KnowDis Data Science in Aug 2024
Interview
I had 2 rounds before I was ghosted by the recruiter.
1. First round had 2 DSA questions. The first one was easy but the second one was medium.
2. Second round was on ML basics and NLP case study.
Interview questions [1]
Question 1
Design a search system using NLP techniques in ML.
I applied online. I interviewed at KnowDis Data Science (Delhi Cantonment) in Dec 2019
Interview
Basic ML concepts, Python , pandas , numpy , Expect questions that test your understanding of fundamental machine learning concepts, algorithms, and statistical techniques. Be prepared to explain concepts like supervised and unsupervised learning, overfitting, bias-variance trade-off, regularization, and more.