TCS
Large multinational IT services and consulting enterprise based in India.
3 Rounds
~14 Days
Medium
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Data Scientist
•
Technical
•
hard
Explain the architecture of a Transformer model. What makes Self-Attention more efficient than RNNs for NLP tasks?
#Transformers
#NLP
#Self-Attention
#LLMs
Data Scientist
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Technical
•
medium
What is the vanishing gradient problem in Deep Learning, and how do modern architectures solve it?
#Neural Networks
#Gradients
#Activation Functions
Machine Learning Engineer
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Technical
•
hard
Explain the Self-Attention mechanism in Transformer architectures. How are the Query, Key, and Value matrices generated and used?
#Transformers
#NLP
#Attention Mechanism
Machine Learning Engineer
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Technical
•
medium
Explain the vanishing and exploding gradient problems in standard RNNs. How do LSTM networks solve this mathematically?
#RNN
#LSTM
#Optimization
Machine Learning Engineer
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Technical
•
hard
A manufacturing client wants to deploy a defect detection deep learning model on edge devices (Raspberry Pi). How do you optimize the model for inference speed and size?
#Edge AI
#Quantization
#Model Pruning
#Computer Vision
Difficulty Radar
Based on recent AI-sourced data.
Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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Think Out Loud
Always explain your thought process before writing code or drawing architecture.