Self-mock 3: 60-min full ML system design (your hardest case)

Interview questions to prep

1. Why a stack here — what LIFO property does the problem exploit?
2. If this uses a monotonic stack, state the monotonic invariant and how it's restored on each push.
3. Walk through complexity: each element is pushed and popped at most once, so the total work is O(n).

Interview questions to prep

1. Walk me through your 7-step framework for any ML system design interview.
2. How do you avoid running out of time on the model section?

Interview questions to prep

1. What are the first five clarifying questions you ask in any ML system design interview?
2. How do you confirm the business metric vs the ML metric without burning 10 minutes on it?

Interview questions to prep

1. How do you map a business metric to an offline ML metric?
2. Walk through three real cases where offline gains didn't translate online.

Interview questions to prep

1. What levers do you pull when accuracy is great but latency misses the budget?
2. Walk through where you'd add caching in a RAG + LLM pipeline to halve P99.

Interview questions to prep

1. How would you design a cascade: cheap model first, expensive only when needed?
2. What's the right verifier for the cheap model's output — and when does it dominate cost?

Interview questions to prep

1. Walk through cold-start strategies for new users vs new items.
2. Compare bandit-based exploration vs content-based bridges for cold start — when does each fit?

Interview questions to prep

1. When would you reach for federated learning vs differential privacy vs on-device inference?
2. What's the accuracy cost of DP-SGD at typical ε values, and how do you decide if it's acceptable?