Machine Learning Interview Questions
Practice the exact questions companies are asking right now.
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Improve classifier with noisy multi-annotator labels
Problem You are given a text dataset for a binary classification task (label in \{0,1\}). Each example has been labeled by multiple human annotators, ...
Design robber detection from surveillance video
You’re a Data Scientist on a team building a computer-vision system for public-safety monitoring. Problem Design an ML system that uses fixed surveill...
Debug and fix a PyTorch Transformer training loop
Minimal Causal LM Debugging and Optimization Context You are given a tiny causal decoder-only language model implemented in PyTorch. It appears to "tr...
Debug a broken Transformer implementation
You are given a small Transformer model implementation (e.g., in PyTorch) plus a tiny training script. The code executes, but the model does not match...
How predict vehicles’ turn direction at intersection?
At an intersection, there are N vehicles stopped or moving slowly. For each vehicle you have historical time-series data up to the current time: - Pos...
Explain LLM post-training methods and tradeoffs
You are asked about LLM post-training (after pretraining on large corpora). Explain a practical post-training pipeline for turning a base model into a...
Build a model using only pandas/numpy
You are given a tabular dataset as a pandas DataFrame df with: - Feature columns (numeric and/or categorical) - A target column y (either binary class...
Predict Bike Dock Demand
You are working on a docked bike-sharing system. Build a model that predicts how many bikes will be checked out from a specific dock in the next hour....
Compare two rare-event detection models statistically
You are evaluating two models (Model A and Model B) for rare-event detection (e.g., fraud, abuse, medical adverse event). Positives are extremely rare...
Debug transformer and train classifier
Debug and Fix a Transformer Text Classifier, Then Train and Evaluate It Context You inherit a small codebase for a transformer-based text classifier. ...
Explain KNN and how to tune it
K-Nearest Neighbors (KNN) fundamentals You are interviewing for a Data Scientist role. 1. Explain how the KNN algorithm works for both classification ...
Explain activations, losses, and Adam
Answer the following ML fundamentals questions: 1) Neural network building blocks - What is a "layer" in a neural network, and what does it compute? -...
Predict bike demand and avoid overfitting
You are given historical data for a city bike-sharing system. Available fields include station_id, hourly timestamp, number of bike pickups and return...
Implement and Debug Backprop in NumPy
Two-Layer Neural Network: Backpropagation and Gradient Check (NumPy) Context You are implementing a fully connected two-layer neural network for multi...
Design multimodal deployment under compute limits
You need to answer a set of questions related to multimodal model deployment and post-training optimization in an interview. Provide systematic explan...
Explain NLP/RL concepts used in LLM agents
You are interviewing for an applied ML role focused on LLM agents and retrieval-augmented generation (RAG). Answer the following conceptual questions ...
Build a Heart Disease Baseline
You are given a tabular dataset for predicting whether a patient has heart disease. The dataset contains a binary target column such as has_heart_dise...
Debug a GRPO training loop and explain ratios
You are given a simplified implementation of a GRPO (Group Relative Policy Optimization) training step for an RLHF-style policy model. The training is...
Design a Homepage Store Recommender
You are designing the homepage store recommendation system for a food-delivery app similar to DoorDash. When a user opens the app, the online request ...
Deep-dive XGBoost handling and overfitting
Technical / ML Deep Dive You used gradient-boosted decision trees (e.g., XGBoost/LightGBM) for a credit risk or response prediction problem. Answer th...