It was an easy interview process. There was just one round with a few questions about my projects and past experience and some stuff related to retrieval augmented generation, LangGraph, Transformers, etc.
I was mostly asked embedding question and llm based question and basic machine learning questions like precesion , recall and f1-score.
So prepare about embeddings as this is important and basic dsa question like checking your understanding about python .
Interview questions [1]
Question 1
What is embeddings ? and have you finetuned any embeddings.
Explain your previous data science projects done, challenges faced, and solutions. Discuss deep learning models—architecture choices, training, optimization techniques, and evaluation metrics. solved medium level coding problems and explain approach.
