How to Prepare for ML Interviews at Indian Companies

ML Interview Preparation

Structured preparation guide for ML interviews in India.

Interview Stages

1. Resume Screen: Projects > Certifications
2. Phone Screen: ML basics, coding
3. Technical Round 1: ML theory + coding
4. Technical Round 2: ML system design
5. Hiring Manager: Fit, experience deep-dive

Topics to Cover

ML Fundamentals

• Bias-variance tradeoff
• Overfitting and regularization
• Cross-validation strategies
• Feature engineering
• Common algorithms (trees, SVM, clustering)

Deep Learning

• Backpropagation mathematics
• CNN architectures and intuition
• RNN/LSTM/Transformer basics
• Attention mechanisms
• Transfer learning

Coding

• Python/NumPy proficiency
• Implement ML algorithms from scratch
• Data manipulation with Pandas
• Basic DSA (arrays, trees, graphs)

System Design

• Design recommendation system
• Design fraud detection system
• Design search ranking
• Scale considerations

Company-Specific Tips

Google/Microsoft

• Strong coding focus
• ML theory depth
• Research paper discussions

Startups (Sarvam, Yellow.ai)

• Practical experience valued
• End-to-end ownership
• Move fast mindset

Product Companies (Flipkart, Swiggy)

• Business impact focus
• A/B testing knowledge
• Product sense

Resources

• Chip Huyen ML Interviews Book
• Designing ML Systems (O'Reilly)
• Made With ML Interview Guide
• LeetCode (easy-medium for ML roles)