Lilly Tech Systems
AI System Design Interview Questions
Prepare for ML system design interviews at FAANG and top tech companies. Each lesson walks through a real interview question using the structured framework interviewers expect: requirements gathering, high-level design, deep dives into critical components, and trade-off discussions with concrete numbers.
Your Learning Path
Start with the interview framework, then practice with progressively harder system design questions that cover the most common FAANG interview topics.
1. How to Approach AI System Design Interviews
The 4-step interview framework (clarify, high-level design, deep dive, trade-offs), 45-minute time management, what interviewers look for, common mistakes, and scoring rubric.
2. Design YouTube Recommendations
1B+ users, <200ms latency. Two-tower candidate generation, deep ranking model, real-time personalization, diversity injection, full architecture with scale calculations.
3. Design ChatGPT
100M+ users. LLM serving architecture, conversation management, streaming responses, safety layers, rate limiting, cost optimization, and multi-model routing.
4. Design Real-Time Fraud Detection
10K TPS, <50ms latency. Real-time + batch feature engineering, model serving pipeline, rule engine, human review loop, feedback loops, false positive management.
5. Design Google Image Search
Billions of images at scale. Embedding generation pipeline, vector indexing (FAISS/ScaNN), query understanding, multi-stage ranking, caching strategies, CDN integration.
6. Design Autonomous Vehicle Perception
Safety-critical design. Sensor fusion architecture, real-time object detection, HD map integration, prediction models, edge computing constraints, redundancy systems.
7. Design TikTok/Instagram Content Feed
500M DAU. Multi-stage ranking pipeline, explore vs exploit balancing, creator-side optimization, real-time signal processing, engagement prediction, ethical considerations.
8. Interview Tips & Common Patterns
Reusable patterns across all questions, how to handle novel problems, communication tips, 4-week practice plan, FAQ accordion with real interviewer perspectives.
What You'll Learn
By the end of this course, you will be able to:
Ace ML System Design Interviews
Structure your answers using the 4-step framework that top candidates use. Know exactly how to spend each minute of a 45-minute interview.
Design End-to-End ML Systems
Draw architecture diagrams for recommendation engines, LLM applications, fraud detection, search, autonomous vehicles, and content feeds with real numbers.
Discuss Trade-Offs Confidently
Articulate why you chose specific approaches over alternatives, backed by concrete latency, cost, and scale calculations that impress interviewers.
Handle Novel Questions
Apply reusable patterns (candidate generation + ranking, feature stores, model serving) to any system design question you have never seen before.