Interview questions

Implement Backprop for a Tiny Network

Companies: OpenAI

ML Coding · Neural Networks & Training

Last reported Apr 2026

Compute Matrix Prefix Products And Gradients

Companies: OpenAI

ML Coding · Neural Networks & Training

Last reported Apr 2026

Derive Backpropagation for Matrix-Product Layers

Companies: OpenAI

Neural Networks & Training

Last reported Feb 2026

Explain what torch.distributed.barrier does

Companies: OpenAI

Neural Networks & Training

Last reported Dec 2025

Design an enterprise RAG assistant for internal docs

Companies: OpenAI

ML System Design · Neural Networks & Training · Retrieval-Augmented Generation

Last reported Dec 2025

Estimate VRAM and compare model parallelism

Companies: Anthropic

Neural Networks & Training

Last reported Nov 2025

Implement and derive backprop from scratch

Companies: Anthropic

ML Coding · Neural Networks & Training

Last reported Sep 2025

Diagnose Transformer training and inference bugs

Companies: OpenAI

Debugging · Neural Networks & Training

Last reported Aug 2025

Debug a transformer training pipeline

Companies: OpenAI

ML Coding · Neural Networks & Training

Last reported Jul 2025

Teaching a Layperson What Deep Learning Is and How It Works

Companies: OpenAI

Communication & Stakeholders · Neural Networks & Training

Last reported Dec 2023

Bias-Variance Tradeoff and Vanishing Gradients in Feedforward Networks

Companies: Pinterest

ML Fundamentals · Neural Networks & Training

Compare Batch Normalization and Layer Normalization

Companies: Snapchat

Debugging · Neural Networks & Training

Explain activations, losses, and Adam

Companies: LinkedIn

Neural Networks & Training · Supervised Learning

Explain BatchNorm, optimizers, and L1/L2

Companies: Snapchat

ML Fundamentals · Neural Networks & Training

Explain bias–variance, overfitting, and vanishing gradients

Companies: Pinterest

ML Fundamentals · Neural Networks & Training

Explain core ML fundamentals and tradeoffs

Companies: Snapchat

ML Fundamentals · Neural Networks & Training

Explain Core ML Interview Concepts

Companies: Amazon

ML Fundamentals · Neural Networks & Training

Explain Layer Normalization in Transformers

Companies: Amazon

Neural Networks & Training · Transformers & Attention

Explain Logistic Regression, Backprop, and Adam

Companies: LinkedIn

Neural Networks & Training · Regression & Statistical Modeling

Explain Neural-Network Regularization and Dropout

Companies: Snapchat

ML Fundamentals · Neural Networks & Training

Explain normalization, regularization, CTR, imbalance handling

Companies: Microsoft

CTR Prediction & Ads ML · Neural Networks & Training

Explain the Forward and Reverse Processes of Diffusion Models

Companies: Mistral AI

Generative Models · Neural Networks & Training