Attention Algorithm Implementation in PyTorch

MLE / ResearchAnthropicLast reported July 2025Low Frequency

Reported: 1× across candidate reports
First seen: July 2025
Last reported: July 2025
Reported outcome: unknown

Problem Overview

The interviewer presents a custom (non-standard) attention algorithm — not the standard scaled dot-product attention — and asks the candidate to implement it from scratch in PyTorch. The code must actually run and pass the provided tests. After the implementation is complete, the interviewer…

2 candidate-reported follow-ups — the exact probes interviewers asked, with the trigger for each
The rest of the problem statement — full requirements, constraints, and edge cases
Approach and trade-offs — what passing candidates did, and the mistakes that sink people

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Verified Source

Every question is reconstructed from multiple independent candidate reports. Verbatim follow-ups, not invented ones.

Codex Fact-Checked

Technical claims, formulas, and scale numbers are reviewed against primary sources.

Interviewer Follow-ups

The exact follow-ups reported by candidates, with the trigger that prompts each one — plus the mistakes that sink people.