Xai·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

Jun 2026Remote

Summary

xAI interview that was basically one long algorithmic puzzle about fault detection. The whole session revolved around a single problem with a lot of follow-up pressure on complexity analysis. Felt more like a research-style discussion than a standard coding screen.

Questions Asked (1)

You have N nodes, some of which are 'bad'. You can call a test function on any subset of at least 2 nodes, which returns true only if all nodes in the subset are good. A node can participate in at most one concurrent test, but multiple non-overlapping tests can run in parallel. Design an algorithm to identify all bad nodes, and analyze its round and call complexity in both sequential and parallel settings.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

This one took me a while to even parse correctly.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints and edge cases, then propose a binary search-like strategy to identify bad nodes efficiently. Analyze the round and call complexity for both sequential and parallel settings, and discuss trade-offs between the two.

Pro tip: Emphasize that in the parallel setting, the round complexity is logarithmic, which is optimal, and highlight how you would handle the case where all nodes are good or all are bad.

1. Clarify the problem

Restate the problem to ensure understanding: N nodes, some bad, test on subset of size >=2 returns true iff all good. Ask about constraints: can we assume at least one bad? What is the goal: minimize rounds, calls, or both?

2. Sequential approach

Propose a binary search strategy: test halves of the set. If a test returns false, at least one bad in that half; recurse. If true, all good in that half. This takes O(log N) rounds and O(N) calls in the worst case.

3. Parallel approach

In each round, partition the current candidate set into pairs (or groups) and test each pair. If a pair tests false, both are bad? Actually, if test on pair returns false, at least one bad; but we need to identify all. Better: test groups of size 2? Wait, need to design correctly.

4. Analyze complexity

For sequential: O(log N) rounds, O(N) calls. For parallel: O(log N) rounds, O(N) calls, but with parallelism, total time O(log N) if enough processors. Discuss trade-offs.

5. Discuss edge cases and optimizations

Consider cases: all good, all bad, single bad. Optimize by stopping early if all good found. Mention that parallel version can be adaptive.

Key Points to Mention

Binary search on the set of nodes to identify bad ones.
Test function returns true only if all nodes in subset are good.
Round complexity: O(log N) in both sequential and parallel.
Call complexity: O(N) in worst case, but can be O(B log N) where B is number of bad nodes? Actually, need to analyze.
Parallelization: multiple non-overlapping tests can run concurrently, reducing rounds.
Trade-offs: sequential uses fewer resources, parallel reduces time but may use more calls.

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