Openai·Machine Learning Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

May 2026Remote

Summary

Interviewed for an ML Engineer role at OpenAI and got a binary search problem dressed up as a dependency versioning question. Felt straightforward at first but the edge case discussion is where things got interesting.

Questions Asked (1)

Given a sorted list of software versions and a predicate that checks if a version satisfies a dependency, find the first (and/or last) working version. Working versions are contiguous in the sorted order. What's the optimal approach and how do you verify its correctness?

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I recognized it as binary search pretty fast, which felt good.

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AI HintsAI Generated

Suggested Approach

Recognize that the problem reduces to finding the boundary of a contiguous region in a sorted array, so binary search is optimal. Explain how to adapt binary search to find the first and last true values of the predicate, and discuss how to verify correctness through edge cases and invariants.

Pro tip: Emphasize that the predicate must be monotonic (all false then all true) for binary search to work; if not, you'd need a different approach. Also, mention that in practice, version strings may require semantic version comparison, not lexicographic.

1. Clarify the problem and assumptions

Confirm that the list is sorted, versions are comparable, and the predicate is monotonic (working versions form a contiguous block). Ask if you need to find the first, last, or both.

2. Choose binary search as the optimal approach

Explain that linear scan is O(n) while binary search is O(log n). Describe how to modify binary search to find the first true (lower bound) and last true (upper bound) by adjusting the search space based on the predicate result.

3. Detail the binary search algorithm

For first working version: maintain low and high, compute mid, if predicate(mid) is true, record mid and search left; else search right. For last working version: if true, record mid and search right; else search left. Handle empty list or no working versions.

4. Discuss correctness and edge cases

Prove correctness by maintaining the invariant that the answer lies within the search range. Test edge cases: all working, none working, single element, and boundary versions.

5. Address practical considerations

Mention that version comparison might need semantic versioning (e.g., 1.10 > 1.9). Also, note that if the predicate is expensive, binary search minimizes calls.

Key Points to Mention

Binary search reduces time complexity from O(n) to O(log n).
Monotonicity of the predicate is crucial for binary search.
Two variants: finding first true (lower bound) and last true (upper bound).
Correctness via loop invariants and termination conditions.
Edge cases: empty list, all true, all false, single element.
Version comparison may require semantic versioning, not simple string comparison.

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