Implement multi-head attention and LLM sampling
Company: Scale AI
Role: Machine Learning Engineer
Category: Coding & Algorithms
Difficulty: easy
Interview Round: Onsite
Quick Answer: This question evaluates implementation and conceptual understanding of Transformer multi-head scaled dot-product attention and next-token sampling for LLMs, including attention masking semantics, softmax numerical stability, time and space complexity, and top-k/top-p with temperature-based sampling.
