Machine Learning Engineer 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, ...
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...
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...
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 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? -...
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 ...
Design RL reward for speed limits
RL Questions (conceptual + practical) You are training an RL agent for driving. Part A — Policy optimization - Explain the difference between PPO and ...
Build model to predict package delivery time
You are building an ML model to predict package delivery time (ETA) for shipments. Given historical shipping data (order created time, origin/destinat...
Train a classifier and analyze dataset
End-to-End Binary Classifier Workflow (EDA → Modeling → Fairness → Report) You are given a labeled tabular dataset and asked to implement a reproducib...
Debug a transformer training pipeline
Diagnose a Diverging PyTorch Transformer Training Run You are given a PyTorch Transformer training pipeline whose loss diverges and validation accurac...
Write self-attention and cross-entropy pseudocode
You are asked to explain core Transformer / deep learning components. Part A — Self-attention pseudocode Write clear pseudocode (not full code) for sc...
Compare NLP tokenization and LLM recommendations
You’re interviewing for an NLP-focused ML role. Part A — NLP fundamentals: tokenization Explain and compare common tokenization approaches used in mod...
Clean OCR data and build an LLM dataset
Problem: OCR data practice (cleaning → LLM-ready data) You are given an OCR dataset intended to train or fine-tune an LLM to improve OCR text quality....
Diagnose Transformer training and inference bugs
Debugging a Transformer That Intermittently Throws Shape/Type Errors and Fails to Converge You are given a Transformer-based sequence model that: - In...
Explain overfitting vs underfitting and fixes
Question 1. What are overfitting and underfitting? 2. How can you diagnose each using training/validation metrics? 3. What are common mitigations for ...
Compare DCN v1 vs v2 and A/B test
Part A — DCN variants You are building a CTR/CVR prediction model for a recommender/ads system using a Deep & Cross Network (DCN). 1. Explain the key ...
Model y from x and interpret distributions
Scenario You are given a dataset with one input feature x and a target y. The interviewer asks: “How would you model this?” Later, you are shown a plo...
Explain bias–variance, overfitting, and vanishing gradients
Answer the following ML fundamentals questions: 1. Bias–variance tradeoff: What are bias and variance? How do they relate to underfitting/overfitting?...
Explain dataset size, generalization, and U-Net skips
You are interviewing for an ML Engineer role in an image/video team. Answer the following conceptual questions clearly and concisely. 1) Small vs. lar...
Explain leakage, missing data, and common losses
Answer the following traditional ML questions: 1. Data leakage - What is data leakage? - Give 2–3 common examples. - How do you prevent or fi...