Ace the LLM Coding Interview (Paperback)

Paperback. Modern LLM interviews are no longer just algorithm drills. You may be asked to implement attention masks, a KV cache, grouped-query attention, RoPE, a decoder-only Transformer, sampling strategies, memory estimates, or preference-optimization losses - from scratch, under time pressure.Ace the LLM Coding Interview is a focused, hands-on guide to the problems that matter most in LLM coding rounds at frontier AI companies and AI-native startups. Every problem uses one compact format: intuition, plain-words math (every formula decoded in plain English), a concrete coding task, a clean Python + NumPy solution, and the follow-up questions interviewers actually ask.Inside: the attention family (masks, scaled dot-product attention, multi-head attention, KV cache, GQA/MQA, RoPE); the full modern architecture (RMSNorm, SwiGLU, pre-norm blocks, a decoder-only mini-GPT, and the generate loop); tokenization and decoding (BPE, temperature, top-k, top-p, beam search); training mechanics (backprop, AdamW, LR schedules, gradient clipping and accumulation); scaling and systems math (KV-cache memory, prefill vs decode, parameter counts, mixed precision, speculative decoding); alignment and RL (SFT, reward models, DPO, PPO/RLHF, GRPO and RLVR); and evaluation (perplexity, passatk, agent evals, and how interviewers grade you).Each chapter ends with a last-day review sheet: formulas to memorize, code templates, shape invariants, and the common mistakes that break solutions.No survey filler. No framework dependency. Just the core implementations you should be able to reproduce on a whiteboard. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…