Apple·Machine Learning Engineer·Technical Phone Screen·Senior

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May 2026

Summary

Apple ML engineer screen that ended up being heavier on string algorithms than I expected. One problem, but it had enough layers to keep me busy for the full slot.

Questions Asked (1)

Given a list of words and a string s, wrap every substring of s that matches any word in the list with bold tags. Adjacent or overlapping matches should be merged into a single pair of tags. How do you approach this, and what are the tradeoffs between a brute-force scan versus a Trie or multi-pattern matching approach?

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

Started with the brute-force: for each word, scan s for all occurrences and mark those index ranges.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., word list size, string length, case sensitivity) and then outline a two-phase solution: first find all matches (using brute-force, Trie, or Aho-Corasick), then merge overlapping intervals and insert tags. Compare the tradeoffs of each matching approach in terms of time/space complexity and practical performance, and justify your choice based on the expected input scale.

Pro tip: Mention that in production systems like Apple's, you'd likely use a precompiled Aho-Corasick automaton for efficiency, but also consider memory constraints and the cost of building the automaton if the word list changes frequently.

1. Clarify requirements and constraints

Ask about input sizes, whether matches are case-sensitive, if words can overlap, and if the output should preserve original formatting. This ensures you design the right solution.

2. Choose a matching strategy

Decide between brute-force scanning (for small inputs), Trie-based matching (for prefix sharing), or Aho-Corasick (for multiple patterns in linear time). Explain the tradeoffs.

3. Find all matches and record intervals

Scan the string and collect start/end indices of all matches. For Trie/Aho-Corasick, this is done in a single pass; for brute-force, it may require nested loops.

4. Merge overlapping intervals

Sort the intervals by start index and merge any that overlap or are adjacent. This ensures a single pair of tags around contiguous matches.

5. Construct the output string

Iterate through the original string, inserting bold tags at the start and end of each merged interval, and return the resulting string.

Key Points to Mention

Time complexity: brute-force O(n * m * k) vs Trie O(n * k) vs Aho-Corasick O(n + m + z) where n is string length, m is total pattern length, k is max word length, z is number of matches.
Space complexity: Trie uses O(m) space, Aho-Corasick adds failure links, brute-force uses O(1) extra space.
Overlap merging: use interval merging algorithm (sort by start, merge if next.start <= current.end).
Edge cases: empty word list, empty string, words that are substrings of others, case sensitivity, Unicode characters.
Practical considerations: building a Trie/Aho-Corasick may be overkill for small inputs; consider precomputation if the word list is static.
Implementation details: avoid modifying the string while scanning; use a list of intervals and then build the result.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.