Top 25 ML System Design Interview Questions

A guide to the pitfalls in ML system design: 25 questions in 6 chapters, from loss functions to feedback loops.

207 pages, 25 questions, 2025. Free.

Each question gives you

  • The interview scenario
  • The trap, explained
  • A technical deep dive
  • Why the common answer fails
  • The solution

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What's inside

Each question is also on this site, with the question and the answer most candidates give.

  1. Loss functions and optimization traps

    1. The Auto-Bidder Paradox
    2. The Multi-Objective Loss Trap
    3. The Softmax Trap
    4. The Flat Loss Trap
    5. The Vanishing Update Paradox
  2. Data quality and distribution

    1. The Data Leakage Trap
    2. The Gradient Drowning Trap
    3. The Semantic Imbalance Trap
    4. The Silent Feature Death
    5. The Silent Graveyard Effect
    6. The P-Value Mirage
  3. Model architecture and training

    1. When Data Is Small, Representation Is King
    2. The Catastrophic Forgetting Trap
    3. The LoRA Knowledge Trap
    4. The Curse of Multilinguality
    5. The Counterintuitive Truth About Quantization and Robustness
  4. Evaluation and validation

    1. The ROC Curve Mirage
    2. The Gallbladder Illusion
    3. The SOTA Trap
  5. System architecture and infrastructure

    1. The Infinite Stream Trap
    2. The Streaming Median Trap
    3. The 10-Minute Horizon
    4. The Database-as-Queue Trap
  6. Production systems and feedback loops

    1. The CTR Feedback Loop Trap
    2. The Greedy Search Trap