1. Coding & Algorithms Expect standard algorithm and data structure problems (like from LeetCode). Emphasis on clean code, optimal solutions, and reasoning. Examples: Implement a cache with O(1) access. Design a rate limiter. Solve graph traversal or dynamic programming problems. 2. Systems Design / ML Systems Design robust, scalable systems—often in AI/ML contexts. Examples: How would you design a distributed training system? How do you deploy and monitor a large language model in production? 3. Machine Learning & Deep Learning (for relevant roles) Deep understanding of models (transformers, diffusion models, etc.) Expect questions about training dynamics, loss functions, and optimization. Examples: Why does layer normalization work better than batch norm in transformers? How would you debug a model that's overfitting?

This was the first coding round after the HR call. It began with a self-introduction, followed by the coding portion, where I worked through the problem and explained my thinking step by step.