Machine Learning Engineer Interview Questions
Master your tech interview with our curated database of real questions from top companies.
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...
Explain parallelism and collectives in training
Parallelism strategies and communication in large-scale training You are designing a distributed training setup for very large neural networks that ca...
Compare float types and design ablation
Floating-point types and ablation study design You are training deep neural networks on modern accelerators that support multiple floating-point forma...
Implement PyTorch training loop
Implement a basic PyTorch training loop You are given a PyTorch neural network model, a DataLoader that yields (inputs, targets) batches, an optimizer...
Explain GRPO-style training for diffusion models
You are given a pretrained image diffusion model that generates images conditioned on text prompts (e.g., a text-to-image model). You now want to fine...
Design ML system for self-driving perception
You are interviewing for a Senior Machine Learning Engineer role on a self-driving car team. They ask you to design a machine learning system for obst...
Solve meeting scheduling and robot cleaning tasks
You are given two independent coding problems. --- Problem 1: Prioritized Meeting Scheduling You are asked to schedule meetings in a single meeting ro...