One question that stood out was about how I would influence AI-driven algorithms and search experiences outside of traditional SEO methods. They were interested in how PR, brand authority, and content strategy can shape visibility and trust in emerging AI ecosystems. Another memorable moment was discussing books and thought leaders who have influenced my perspective on storytelling and brand building. It was clear they valued curiosity and intellectual range as much as technical skill.
Solve a coding challenge that required both algorithmic thinking and efficient Python implementation under a strict time limit.
Round 1: Breadth Assessment This round evaluated the width of my knowledge across the Data Science spectrum. The structure was: Personal introduction Project walkthrough (one detailed project explanation) Technical questions spanning: Machine Learning: Data preprocessing and model evaluation Deep Learning: Optimizers and Gradient Descent Generative AI: RAG (Retrieval-Augmented Generation) and LLMs Coding problems: Printing series patterns and list/dictionary comprehension Difficulty level: Easy to moderate. Round 2: Deep Dive Technical Round This round went significantly deeper into specialized topics: Sentence transformers and their applications Benchmarking and evaluation methodologies RAG architecture and implementation Evaluation frameworks (RAGAs, DSPy) Transformer architecture fundamentals Advanced concepts: Training different word embeddings, contextual awareness, positional encoding
They asked more in depth of Mathematics related to AI Machine learning.
AI related interview questions
my experience with machine learning
1. Tell me about transformers
How to handle data if it is not balanced.
Explain me loss? Go over attention for someone who doesn’t know the technical details.
Tell us about yourself(non technical) why iamneo? why coimbatore? How is AI affecting the jobs?
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