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Snapchat·Machine Learning Engineer·Technical Phone Screen·Senior

Senior
Apr 2026

Summary

Snapchat ML Engineer interview had at least one coding round with a classic recursion problem. Nothing too wild but the backtracking angle is easy to fumble if you haven't thought about it carefully beforehand.

Questions Asked (1)

Q1

Given an integer n, generate all combinations of n pairs of well-formed parentheses and return them as a list of strings.

Algorithms & Data Structures
Author's notes

The recursive backtracking approach is what they're looking for: track how many open and close parens you've placed, and only add a closing paren when the close count is less than the open count.

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AI HintsAI Generated

Suggested Approach

Use backtracking to build valid parentheses strings incrementally, ensuring at each step the number of closing parentheses never exceeds opening ones. Track the counts of open and close parentheses used, and only add '(' if open < n, and ')' if close < open. When the string length reaches 2n, add it to the result.

Pro tip: Discuss the time complexity as O(4^n / sqrt(n)) (the nth Catalan number) and mention that this is optimal since you must generate each valid string. Also, briefly note how this combinatorial generation could be relevant to ML tasks like generating structured outputs or parsing expressions.

1. Clarify and Define

Confirm that n is a non-negative integer and that the output should be a list of strings. Define what constitutes a well-formed parentheses string: equal number of '(' and ')', and at any prefix, the number of ')' does not exceed '('.

2. Choose Backtracking

Explain that backtracking is ideal because it explores all valid combinations by making choices and undoing them. It prunes invalid paths early, avoiding unnecessary work.

3. Outline Recursive Logic

Describe the recursive function: parameters are the current string, count of open parentheses, and count of close parentheses. At each call, if open < n, add '(' and recurse; if close < open, add ')' and recurse. Base case: when string length == 2n, add to result.

4. Analyze Complexity

State that the number of valid combinations is the nth Catalan number, so time complexity is O(4^n / sqrt(n)) and space complexity is O(n) for recursion depth (excluding output storage).

5. Test with Example

Walk through n=3 to show how the algorithm generates all 5 valid strings, ensuring no duplicates and all are well-formed.

Key Points to Mention

  • Backtracking approach with pruning to avoid invalid strings
  • Maintaining counts of open and close parentheses to enforce validity
  • Base case: when the string length reaches 2n
  • Time complexity: O(4^n / sqrt(n)) (Catalan number)
  • Space complexity: O(n) for recursion stack
  • Edge case: n=0 returns [""]

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