Hugging Face Coding Interview Questions
25 Hugging Face coding interview problems with full optimal solutions — 8 easy, 12 medium, 5 hard. Every problem ships with multiple approaches (brute-force first, then the optimal), complexity tables for each, company-specific tips on what an Hugging Face interviewer values, and a FAQ section.
Showing 2 problems of 25
- #146mediumvery frequently asked
146. LRU Cache
Design a cache that evicts the least-recently-used entry when full. Hugging Face uses this because it mirrors a real problem they solve at scale — caching tokenizer outputs and hosted model inference results where stale entries must be evicted under memory pressure to serve millions of API requests efficiently.
- #208mediumvery frequently asked
208. Implement Trie (Prefix Tree)
Build a prefix tree that supports insert, search, and startsWith. Hugging Face uses this because a Trie is the canonical data structure for prefix-based token lookup in tokenizer vocabularies — understanding it deeply signals you can reason about the internals of text processing infrastructure.