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 12 problems of 25
- #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.
- #15mediumfrequently asked
15. 3Sum
Find all unique triplets in an array that sum to zero. Cohere asks this to test systematic duplicate-elimination alongside the two-pointer technique — skills that transfer directly to deduplicating retrieved document clusters in a RAG pipeline.
- #49mediumfrequently asked
49. Group Anagrams
Group strings that are anagrams of one another. Cohere asks this because canonical-key hashing mirrors how embedding models deduplicate semantically-equivalent queries before routing them to a retrieval index.
- #56mediumfrequently asked
56. Merge Intervals
Merge all overlapping intervals in a list. Cohere asks this because interval merging directly models context-window deduplication, log event collapsing, and bounding-box merging in document-layout analysis for enterprise RAG systems.
- #139mediumfrequently asked
139. Word Break
Determine if a string can be segmented into words from a dictionary. Cohere asks this because the DP segmentation pattern directly models how subword tokenisers decide optimal byte-pair-encoding splits during vocabulary construction.
- #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.
- #200mediumfrequently asked
200. Number of Islands
Count the number of connected components in a binary grid. Cohere asks this to test graph traversal — the same connected-component reasoning used when clustering retrieved document chunks into coherent topic groups.
- #207mediumfrequently asked
207. Course Schedule
Detect whether a set of course prerequisites can all be satisfied — i.e., detect a cycle in a directed graph. Cohere asks this because topological ordering of task dependencies mirrors pipeline DAG scheduling for multi-step RAG and agentic workflows.
- #238mediumfrequently asked
238. Product of Array Except Self
Compute the product of all elements except each element itself, without division. Cohere asks this because the prefix/suffix product pattern is the same technique used in attention-mask generation and cumulative probability normalisation in beam search.
- #322mediumfrequently asked
322. Coin Change
Find the minimum number of coins that sum to a target amount. Cohere uses this to assess unbounded knapsack DP — the same optimisation framework underlying minimum-edit decoding and optimal token-budget allocation in constrained generation.
- #347mediumfrequently asked
347. Top K Frequent Elements
Return the k most frequent elements in an array. Cohere asks this because frequency-based ranking is central to term-frequency scoring, vocabulary selection during tokeniser training, and log-aggregation pipelines.
- #692mediumfrequently asked
692. Top K Frequent Words
Return the k most frequent words, with lexicographic tiebreaking. Cohere includes this because frequency-ranked vocabulary selection with deterministic tiebreaking is exactly how tokeniser vocabularies are built from a training corpus.