Quick Overview

This coding question tests practical implementation of top-p (nucleus) sampling, a core decoding strategy in large language models. It evaluates NumPy proficiency including numerically stable softmax, cumulative probability thresholding, and reproducible stochastic sampling — skills central to machine learning engineering roles.

Implement Top-p (Nucleus) Sampling in NumPy

Company: Amazon

Role: Applied Scientist

Category: Coding & Algorithms

Difficulty: medium

Interview Round: Onsite

Overview: This coding question tests practical implementation of top-p (nucleus) sampling, a core decoding strategy in large language models. It evaluates NumPy proficiency including numerically stable softmax, cumulative probability thresholding, and reproducible stochastic sampling — skills central to machine learning engineering roles.

Read the full Amazon Applied Scientist interview experience this question came from

Loading…