Cohere Coding Interview Questions
25 Cohere 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 Cohere interviewer values, and a FAQ section.
Showing 7 problems of 25
- #1easyvery frequently asked
1. Two Sum
Given an integer array and a target, return indices of the two numbers that add up to the target. Cohere asks this as a warm-up because hash-map lookup is the foundation of embedding deduplication and nearest-neighbor retrieval at scale.
- #3mediumvery frequently asked
3. Longest Substring Without Repeating Characters
Find the length of the longest substring with all unique characters. Cohere asks this because sliding-window deduplication is core to tokenization span selection and context-window management in production language-model serving.
- #4hardoccasionally asked
4. Median of Two Sorted Arrays
Find the median of two sorted arrays in O(log(m+n)) time. Cohere asks this hard problem because binary search on partition boundaries is the same mathematical discipline applied to efficient percentile estimation in model evaluation pipelines.
- #127hardoccasionally asked
127. Word Ladder
Find the shortest transformation sequence from one word to another, changing one letter at a time. Cohere asks this because BFS over an implicit graph is the same reasoning used to find shortest edit-distance paths between token sequences in vocabulary-constrained generation.
- #146mediumvery frequently asked
146. LRU Cache
Design a cache that evicts the least-recently-used entry when full. Cohere asks this because LRU caching is a first-class concern in embedding serving — caching recently-requested embedding vectors avoids redundant inference and reduces GPU cost at scale.
- #283easyoccasionally asked
283. Move Zeroes
Move all zeroes to the end of an array while preserving the relative order of non-zero elements. Cohere asks this to test in-place two-pointer discipline — the same pattern used when compacting sparse token arrays in a batched inference engine.
- #642hardoccasionally asked
642. Design Search Autocomplete System
Design a real-time autocomplete system that suggests the top-3 most frequently typed sentences matching the current prefix. Cohere asks this design-heavy hard problem because prefix-indexed retrieval with frequency ranking is the core of their enterprise search and query-suggestion products.