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Snapchat·Machine Learning Engineer·Technical Phone Screen·Senior

Senior
Apr 2026

Summary

Snapchat ML engineer interview with a tree traversal problem that looks straightforward until you realize you need parent pointers and they don't exist natively in a binary tree. Not a bad round, just required some setup work before the actual logic.

Questions Asked (1)

Q1

Given a binary tree with unique node values, a target value, and a list of jump offsets, find the target node and then repeatedly walk upward by the number of levels specified in each jump. Return the values of the nodes you land on, stopping early if you'd go past the root.

Algorithms & Data Structures
Author's notes

First instinct was to just recurse and track depth, but the jumps aren't cumulative from root, they're sequential hops from wherever you currently are.

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AI HintsAI Generated

Suggested Approach

First, traverse the tree to find the target node while recording each node's parent and depth, or build a parent map via BFS/DFS. Then, starting from the target, repeatedly move up by the given jump offsets using the parent pointers, stopping if the jump would exceed the root. Collect and return the values of the nodes landed on.

Pro tip: Clarify whether the jump offsets are absolute levels or relative to the current node, and confirm if the target node itself should be included in the output. Also, discuss edge cases like empty tree, target not found, or jumps larger than the remaining depth.

1. Clarify requirements and edge cases

Ask about input format, whether the tree is binary, if jumps are absolute or relative, and what to return if the target is missing or jumps exceed depth. Confirm if the target node is included in the result.

2. Choose traversal to locate target and build parent map

Use BFS or DFS to find the target node while storing parent pointers for each node (e.g., in a hash map). Alternatively, record the path from root to target to enable upward traversal.

3. Simulate upward jumps

Starting from the target, for each jump offset, move up that many levels using parent pointers. If the number of levels exceeds the remaining depth to the root, stop early and do not include that node.

4. Collect and return results

Append the value of each node landed on to a result list. Ensure the order matches the sequence of jumps. Return the list.

5. Analyze complexity and optimize if needed

Discuss time and space complexity: O(N) to build parent map, O(K) for K jumps, where K is number of offsets. Space O(N) for parent map. Consider if multiple queries or large trees require preprocessing.

Key Points to Mention

  • Parent pointers or path recording to enable upward traversal
  • Handling jumps that exceed the root (stop early)
  • Edge cases: empty tree, target not found, single node, large jumps
  • Time and space complexity analysis
  • Choice of BFS vs DFS for finding target and building parent map
  • Clarifying whether the target node is included in the output

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