Machine Learning Engineer Interview Questions
Practice the exact questions companies are asking right now.
Explain ML model fundamentals
Comprehensive ML Concepts: Logistic Regression, Naive Bayes, Transformers, Multi-class Metrics, Bagging vs Boosting Context You are interviewing for a...
Discuss Transformer LLM Design
System-Design-Oriented LLM Question Context: You are designing, fine-tuning, and operating a Transformer-based large language model (LLM) that answers...
Explain key ML theory and techniques
Onsite Machine Learning Engineer: Mixed Topics You are asked to answer concisely but with depth across the following topics: 1) XGBoost Parallel Compu...
Design feedback-driven recommender
Design: Contextual Bandit Recommendation with Online Learning You are designing an online learning recommendation system. At each user interaction: - ...
Count subarrays summing to target
Question LeetCode 560. Subarray Sum Equals K – Given an integer array nums and an integer k, return the total number of continuous subarrays whose sum...
Discuss ML infrastructure fundamentals
ML System Design: Infra Stack, Feature Store, Reproducibility, and Monitoring Context: You are designing and operating a machine learning platform tha...
Discuss dissertation and supervision
Behavioral Interview: Dissertation Overview and Supervisor Collaboration Context You are in an onsite behavioral and leadership round for a Machine Le...
Design query generation system
System Design: Query-Generation to Maximize CTR Context You are designing a real-time system that generates and ranks search query suggestions shown t...
Explain ML statistics and model design concepts
Technical Phone Screen: Theory + System Design Probability and Statistics 1. Define a moment generating function (MGF) and explain how it is used. 2. ...
Solve matrix rotation and 1-D illumination
Question LeetCode 48. Rotate Image – rotate an n×n matrix 90° clockwise (extra space allowed). Find the point(s) with the maximum number of illuminate...
Find earliest supporting version under constraints
You are given version strings formatted as {major}.{minor}.{patch}, e.g., "103.003.03". Each version either supports a feature or not. You may call is...
Build and evaluate click prediction models
Click-Through Rate (CTR) Prediction: Build, Compare, and Justify Models Context You are given a tabular dataset for binary click prediction (click = 1...
Design a harmful content detection system
System Design: End-to-End Harmful Content Detection (Multilingual, Multimodal) Context You are designing a safety system for a large, mobile-first, ep...
Train LinearSVC to beat baseline accuracy
Task: Train and Evaluate a LinearSVC to Beat a Baseline Context You are given a binary or multi-class classification dataset split into train and hidd...
Design a restaurant recommendation system
ML System Design: Restaurant Recommendations (Delivery App) You are designing a restaurant recommendation system for a food delivery marketplace (e.g....
Explain ML evaluation, sequence models, and optimizers
Scenario An interviewer is deep-diving into an ML project you built (you can assume it is a supervised model unless specified otherwise). They want yo...
Answer core behavioral questions using STAR
Prepare structured answers (use STAR: Situation, Task, Action, Result) for the following common behavioral prompts: 1. Most proud project: Describe a ...
Test whether two user populations differ
Problem You are given two groups of users: - Group A: North America users - Group B: Europe users Each user has a vector of continuous features (e.g.,...
Design a search query autocomplete system
Question Design a search autocomplete system that suggests completions as the user types. Requirements - Sub-100ms latency per keystroke. - Suggestion...
Explain core ML concepts and lifecycle
You are interviewing for an ML Engineer role. Answer the following (conceptually; no code required): 1) Bias–variance tradeoff - What are bias and var...