Implement Softmax Cross-Entropy Forward and Backward Passes and a Training Loop

Quick Overview

Implement the forward and backward passes of softmax with cross-entropy loss from scratch, then write a full training loop for a linear classifier. Tests numerical stability, the logits gradient, vectorized code, gradient checking and minibatch training.

Implement Softmax Cross-Entropy Forward and Backward Passes and a Training Loop

Company: Waymo

Role: Machine Learning Engineer

Category: Machine Learning

Difficulty: medium

Interview Round: Onsite

Overview: Implement the forward and backward passes of softmax with cross-entropy loss from scratch, then write a full training loop for a linear classifier. Tests numerical stability, the logits gradient, vectorized code, gradient checking and minibatch training.

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Waymo
Sep 10, 2026
mediumMachine Learning EngineerOnsiteMachine Learning
32
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