Meta·Machine Learning Engineer·Technical Phone Screen·Senior

Senior

May 2026

Summary

Meta MLE interview with a debugging task on a friend recommendation system. Pretty focused, just one coding problem but it had enough edge cases to trip you up if you weren't paying attention.

Questions Asked (1)

You're given a friend recommendation codebase with a buggy function that determines whether a candidate is a valid recommendation for a user. Fix it so it correctly excludes the user themselves and anyone already in their friend list, then verify against the provided unit tests.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The bug itself wasn't hard to spot once I read the code carefully.

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AI HintsAI Generated

Suggested Approach

First, clarify the function's contract and edge cases, then trace the buggy logic to identify where self and existing friends are not properly excluded. Fix the condition using set-based membership checks, and run the provided unit tests to confirm correctness and consider additional edge cases.

Pro tip: After fixing the bug, discuss how this validation logic scales to millions of users and how it might integrate with a real-time recommendation pipeline, showing you think beyond the immediate fix.

1. Clarify requirements and edge cases

Restate the function's purpose: return True only if the candidate is not the user and not already in the user's friend list. Identify edge cases like empty friend lists, self-recommendation, and duplicate entries.

2. Analyze the buggy code

Read the function to locate the flawed condition. Common bugs include using 'or' instead of 'and', missing self-check, or checking membership against the wrong data structure.

3. Implement the fix

Correct the logic using clear, efficient checks: e.g., 'candidate != user and candidate not in friends_set'. Convert the friend list to a set for O(1) lookups if performance matters.

4. Verify with unit tests

Run the provided unit tests to ensure the fix passes. If tests are missing, write additional tests covering self, existing friend, non-friend, and empty friend list scenarios.

5. Discuss scalability and trade-offs

Explain how the solution scales: using a set for friend lookup is O(1) per check, but memory may be a concern for very large friend lists. Consider caching or approximate membership if needed.

Key Points to Mention

Correct boolean logic: use AND to combine exclusion conditions, not OR.
Data structure choice: set vs list for friend membership checks and its impact on time complexity.
Edge cases: self-recommendation, empty friend list, candidate already a friend, duplicate friends.
Unit test verification: run provided tests and add missing edge-case tests.
Scalability: handling large friend lists and real-time recommendation systems.
Code readability: clear variable names and comments explaining the exclusion logic.

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