Interview questions

Explain a favorite model end-to-end

Companies: Google

Explain a Markov Decision Process

Companies: Voleon

Explain activations, losses, and Adam

Companies: LinkedIn

Neural Networks & Training · Supervised Learning

Explain an ML project end-to-end with tradeoffs

Companies: Roblox

Explain and quantify bias-variance tradeoff

Companies: Roku

Explain and Reduce Position Bias in Ranking

Companies: Reddit

Model Evaluation · Ranking Models

Explain and test completion-rate gaps

Companies: Uber

Hypothesis Testing · Metric Diagnostics

Explain and tune decision trees robustly

Companies: Point72

Model Evaluation · Supervised Learning

Explain and tune XGBoost; prevent overfitting

Companies: TikTok

Explain AUC, activations, ensembles, and imbalance

Companies: Boston Consulting Group

ML Fundamentals · Model Evaluation

Explain AUC, imbalance, losses, and networks

Companies: Boston Consulting Group

Model Evaluation · Supervised Learning

Explain BatchNorm, optimizers, and L1/L2

Companies: Snapchat

ML Fundamentals · Neural Networks & Training

Explain bias-variance and evaluate a classifier

Companies: Microsoft

ML Fundamentals · Model Evaluation

Explain bias-variance, calibration, and model drift

Companies: NVIDIA

ML Fundamentals · Model Monitoring & Drift

Explain bias–variance, overfitting, and vanishing gradients

Companies: Pinterest

ML Fundamentals · Neural Networks & Training

Explain Causal-Inference Techniques in Your Machine Learning Project

Companies: Cvs Health

Explain Chunking for Financial RAG

Companies: Morgan Stanley

Explain CNN shapes, params, and trade-offs

Companies: Apple

Explain Common Machine Learning Tradeoffs

Companies: Ansys

Explain Core ML Concepts

Companies: Instacart, JPMorgan, Snapchat

ML Fundamentals · Regression & Statistical Modeling · Supervised Learning

Explain core ML concepts and diagnostics

Companies: Amazon

Experiment Analysis & Readout · ML Fundamentals