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Meta·Machine Learning Engineer·Technical Phone Screen·Senior

Senior
Jun 2026

Summary

Meta ML engineer interview with a classic array problem. Nothing too wild but the efficiency constraint is where they actually care.

Questions Asked (1)

Q1

Given an array of integers, find the next greater element for each element in the array efficiently.

Algorithms & Data Structures
Author's notes

Jumped straight to brute force in my head and had to stop myself.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints (e.g., array size, whether circular, handling duplicates) and then propose an O(n) solution using a monotonic stack. Explain the algorithm step-by-step, analyze time and space complexity, and discuss potential optimizations or variations.

Pro tip: Mention that the monotonic stack approach is optimal and can be adapted for circular arrays or to find previous greater elements. Also, relate it to ML engineering tasks like feature engineering or sequence processing to show practical relevance.

1. Clarify requirements

Ask about input size, whether the array is circular, how to handle duplicates, and expected output format (e.g., return array of next greater or -1 if none).

2. Propose efficient algorithm

Describe the monotonic stack approach: iterate through the array, maintain a stack of indices with decreasing values, and for each element, pop and assign next greater until stack top is greater.

3. Walk through example

Trace the algorithm on a small example (e.g., [2,1,2,4,3]) to demonstrate correctness and how the stack evolves.

4. Analyze complexity

State that each element is pushed and popped at most once, giving O(n) time and O(n) space in the worst case.

5. Discuss extensions

Mention variations like circular arrays (iterate twice), previous greater element, or using the same pattern for other problems (e.g., daily temperatures).

Key Points to Mention

  • Monotonic stack (decreasing order) for O(n) time
  • Handling of duplicates and edge cases (empty array, all decreasing)
  • Time and space complexity analysis
  • Comparison with brute-force O(n^2) approach
  • Potential variations: circular array, previous greater element
  • Relevance to ML engineering: efficient data preprocessing, feature extraction from sequences

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