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Meta·Machine Learning Engineer·Technical Phone Screen·Senior

Senior
May 2026

Summary

Meta ML engineer interview with a classic tree problem. Not much context given but it felt like a technical phone screen type situation.

Questions Asked (1)

Q1

Given two nodes in a binary tree, find their first common ancestor.

Algorithms & Data Structures
Author's notes

Knew this problem but still fumbled the edge cases a bit.

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AI HintsAI Generated

Suggested Approach

Clarify the problem definition and constraints, then discuss both recursive and iterative approaches. For a binary tree (not necessarily BST), a recursive post-order traversal that returns the node if it matches either target or if both subtrees return non-null is optimal. Analyze time and space complexity, and mention edge cases like when one node is an ancestor of the other.

Pro tip: Demonstrate awareness of the trade-offs between different approaches (e.g., using parent pointers vs. recursion) and relate the problem to real-world ML scenarios like dependency graphs or model hierarchies to show practical insight.

1. Clarify the problem

Ask if the tree is a binary search tree (BST) or a general binary tree, if nodes have parent pointers, and if the nodes are guaranteed to be in the tree. This determines the optimal approach.

2. Outline approaches

Discuss possible methods: (1) Recursive post-order traversal for general binary tree, (2) Using parent pointers and finding intersection of paths, (3) For BST, using value comparisons to navigate. Choose the most efficient based on constraints.

3. Detail the chosen algorithm

For general binary tree, explain the recursive function that returns the node if it matches either target or if both left and right subtrees return non-null. Walk through an example to illustrate.

4. Analyze complexity

State time complexity O(n) and space complexity O(h) for recursion, where h is tree height. Mention that iterative approaches can reduce space to O(1) if parent pointers exist.

5. Handle edge cases

Discuss cases: one node is ancestor of the other, nodes not present, empty tree, and duplicate values. Explain how the algorithm handles them.

Key Points to Mention

  • Definition of lowest common ancestor (LCA): the deepest node that has both nodes as descendants.
  • Recursive post-order traversal approach: return node if it matches either target, else recurse left and right; if both return non-null, current node is LCA.
  • Time and space complexity: O(n) time, O(h) space for recursion; can be O(1) space with parent pointers and iterative approach.
  • Handling edge cases: one node is ancestor of the other, nodes not in tree, empty tree.
  • Alternative approaches: using parent pointers to find intersection of paths, or using BST properties if applicable.
  • Real-world relevance: LCA in dependency graphs, model hierarchies, or version control systems (e.g., Git).

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