How do I approach Data Manipulation (SQL/Python) interview questions?

Data Manipulation (SQL/Python) questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master data manipulation (sql/python) interviews.

What difficulty level is this interview question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Onsite rounds at OpenAI.

What role is this question designed for?

This question is commonly asked for Machine Learning Engineer candidates at OpenAI during technical interviews.

Implement vectorized NumPy ops and explain broadcasting

Last updated: Mar 29, 2026

Quick Overview

This question evaluates proficiency in vectorized numerical computing with NumPy, understanding of broadcasting semantics, and awareness of numerical stability and algorithmic time/space complexity when manipulating high-dimensional arrays.

OpenAI

Aug 11, 2025, 12:00 AM

Machine Learning Engineer

Onsite

Data Manipulation (SQL/Python)

Implement vectorized NumPy code for: (a) computing pairwise cosine similarity between two real-valued matrices X (shape n×d) and Y (shape m×d) without explicit Python loops; (b) computing a numerically stable softmax for a 2D array along the last axis; (c) explaining how broadcasting works if X has shape (n, 1, d) and Y has shape (1, m, d). Analyze time and space complexity, and discuss pitfalls such as unintended broadcasting, dtype issues, and memory usage.

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