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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Each question is also on this site, with the question and the answer most candidates give.
- The Tokenizer Trap in Domain-Specific LLM Training
- Speculative Decoding for Lossless Inference Acceleration
- Scaling Laws for Compute-Optimal Model Training
- Stabilizing Deep Transformers with Pre-Layer Normalization
- Byte Pair Encoding for Compute Efficiency in Transformers
- KV Cache Bottlenecks in High-Throughput LLM Systems
- Maximal Update Parametrization for Hyperparameter Transfer
- The Contaminated Benchmark Trap
- Overcoming the Memory Wall in Transformer Attention Mechanisms
- Thinking Mode Fusion for Adaptive Reasoning in Language Models
- The Alignment Tax in RLHF
- Mixture of Experts Router Collapse
- Weight Decay as an Optimization Control in Large Language Model Training
- The Dual Phases of LLM Inference: Compute-Bound Prefill and Memory-Bound Generation
- The FLOPs Fallacy in LLM Inference Optimization
- Correct Application of Rotary Position Embeddings (RoPE) in Transformer Models
- The “Divine Benevolence” Fallacy in Activation Functions
- The Throughput–Latency Paradox in LLM Inference
- Data Curation Pipelines for Frontier Language Models
- Data Curation in LLM Fine-Tuning
- The GRPO Length Normalization Trap
- The Asynchronous Execution Trap in GPU Kernel Benchmarking
- The Mantissa Trap in Mixed Precision Training
- The Computational Asymmetry of Backpropagation
- The Leaderboard Illusion