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Meta·Machine Learning Engineer·Technical Phone Screen·Senior

Senior
Jun 2026

Summary

Meta ML Engineer interview with a tree problem that looks straightforward but has a few ways to trip you up if you're not careful about the base cases.

Questions Asked (1)

Q1

Given a binary tree and two nodes p and q, find their lowest common ancestor (the deepest node that has both as descendants, where a node can be its own descendant).

Algorithms & Data Structures
Author's notes

Classic problem but I still fumbled the edge case where one of the nodes IS the ancestor.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., whether parent pointers exist, if nodes are guaranteed present) and then present a recursive solution that traverses the tree, returning the node if it matches p or q, and otherwise combining results from left and right subtrees. Explain that the first node where both subtrees return non-null is the LCA, and analyze time and space complexity.

Pro tip: Mention that this approach assumes both nodes exist; if not, you can add a post-check to verify their presence. Also, relate the problem to real-world ML scenarios like finding common ancestors in decision trees or hierarchical taxonomies.

1. Clarify constraints and assumptions

Ask if the tree is binary, if nodes have parent pointers, if p and q are guaranteed to be in the tree, and if the tree can be empty. This shows thoroughness and avoids incorrect assumptions.

2. Outline recursive strategy

Explain that you'll traverse the tree recursively: if the current node is null or matches p or q, return it; otherwise, recurse left and right. If both return non-null, the current node is the LCA; if only one returns non-null, propagate that up.

3. Walk through an example

Trace the algorithm on a small tree (e.g., root with left and right children) to demonstrate correctness, highlighting how the LCA is identified when both subtrees return non-null.

4. Analyze complexity

State that time complexity is O(n) in the worst case (visiting each node once) and space complexity is O(h) for recursion stack, where h is tree height (O(n) worst case for skewed tree).

5. Discuss edge cases and extensions

Cover edge cases: one node is ancestor of the other, p or q is root, tree is skewed. Mention alternative approaches (e.g., using parent pointers to find intersection) and trade-offs.

Key Points to Mention

  • Recursive post-order traversal to find LCA
  • Base case: return node if it matches p or q, or if null
  • Combining results: if both left and right return non-null, current node is LCA
  • Time complexity O(n), space complexity O(h)
  • Handling cases where one node is ancestor of the other
  • Assumption that both nodes exist; if not, need additional check

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