Top 25 LLM System Design Interview Questions

25 LLM system design questions from senior and staff interviews for ML, LLM and AI infrastructure roles.

55 pages, 25 questions, November 2025. Free.

Each question gives you

  • The interview question
  • The common wrong answer
  • How it actually works
  • The key paper to cite

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What's inside

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

    1. The Tokenizer Trap in Domain-Specific LLM Training
    2. Speculative Decoding for Lossless Inference Acceleration
    3. Scaling Laws for Compute-Optimal Model Training
    4. Stabilizing Deep Transformers with Pre-Layer Normalization
    5. Byte Pair Encoding for Compute Efficiency in Transformers
    6. KV Cache Bottlenecks in High-Throughput LLM Systems
    7. Maximal Update Parametrization for Hyperparameter Transfer
    8. The Contaminated Benchmark Trap
    9. Overcoming the Memory Wall in Transformer Attention Mechanisms
    10. Thinking Mode Fusion for Adaptive Reasoning in Language Models
    11. The Alignment Tax in RLHF
    12. Mixture of Experts Router Collapse
    13. Weight Decay as an Optimization Control in Large Language Model Training
    14. The Dual Phases of LLM Inference: Compute-Bound Prefill and Memory-Bound Generation
    15. The FLOPs Fallacy in LLM Inference Optimization
    16. Correct Application of Rotary Position Embeddings (RoPE) in Transformer Models
    17. The “Divine Benevolence” Fallacy in Activation Functions
    18. The Throughput–Latency Paradox in LLM Inference
    19. Data Curation Pipelines for Frontier Language Models
    20. Data Curation in LLM Fine-Tuning
    21. The GRPO Length Normalization Trap
    22. The Asynchronous Execution Trap in GPU Kernel Benchmarking
    23. The Mantissa Trap in Mixed Precision Training
    24. The Computational Asymmetry of Backpropagation
    25. The Leaderboard Illusion