Machine Learning Engineer ML System Design Interview Questions
Practice 179 real ML System Design interview questions for Machine Learning Engineer roles. From companies including OpenAI, Meta, Amazon, Snapchat, Google.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Design a game genre classifier
Design an end-to-end machine learning system that classifies a video game into one or more genres from scratch. Assume you are building this for a gam...
Design an end-to-end training framework
Design an End-to-End Time-Series Forecasting Framework (PyTorch) You are tasked with designing a production-grade, end-to-end framework for training a...
Design an ML search system with RAG
System Design: ML-Powered Enterprise Search with RAG Design an ML-powered enterprise search system using Retrieval-Augmented Generation (RAG) under th...
Design Harmful Content and OOM Detection
Design two machine learning systems: 1. Harmful content detection for LLM applications: Build a system that detects harmful user inputs or model outpu...
Design a model to choose dynamic K
Problem You are building a recommender system with a two-stage ranking pipeline: 1. Candidate retrieval (recall): fetch top-K candidates for a request...
Design systems for global request detection and labeling
Answer the following ML system design questions. State assumptions, propose an architecture, and discuss scaling, latency, and reliability. 1) Global ...
Implement a trie-based tokenizer
Design and Implement a Trie-Based Subword Tokenizer for LLM Pretraining Context You are building a subword tokenizer for a large-scale LLM pretraining...
Improve LLM reasoning for a domain task
You are building an LLM-powered product for a domain-specific task that requires multi-step reasoning. The base model does reasonably well on easy exa...
Design an OOD detection system
Prompt You are building a product that uses an ML classifier in production (e.g., for routing, ranking, safety, fraud, or categorization). Over time, ...
Design a video recommendation system
Scenario You are designing an ML-driven video recommendation product (home feed + “up next”) for a consumer app. The interviewer focuses heavily on in...
Design Detection Systems for Risk and Safety
The machine learning system design rounds focused on designing end-to-end production systems for several detection problems: 1. Bank fraud detection: ...
Design a traditional fraud detection system
Design an End-to-End Real-Time Payments Fraud Detection System Context: You are designing a fraud detection system for a large-scale online payments p...
Design agentic workflow to generate a 1-hour movie
Prompt You’re asked to design an agentic workflow (multiple LLM/tools acting as “agents” under an orchestrator) that can generate a ~60-minute movie f...
Design a feed ranking system
Design a machine-learning-based feed ranking system for a consumer product. The system should rank candidate posts or items for a user's home feed in ...
Debug MNIST denoiser training
Debugging a Colab Denoising Network on MNIST Goal: Make a Colab notebook that trains a denoising neural network on MNIST such that: - (a) the training...
Design a fraud detection system
Scenario You are designing an end-to-end fraud detection system for an online platform (e.g., e-commerce marketplace, payments, account signup, or ad ...
Design a RAG system end to end
Design a Retrieval‑Augmented Generation (RAG) System for Enterprise Text Context You are building a production RAG system that answers employee questi...
Design a production RAG system
Question Design a production retrieval-augmented generation (RAG) system for enterprise document QA. Walk through the end-to-end architecture and just...
Design Harmful Content Detection
Design an end-to-end machine learning system to detect harmful user-generated content on a large online platform. Assume the platform accepts text and...
How would you build an image classifier with dirty data?
Scenario You are asked to build an image classification model (single-label, multi-class) for a product team. The image dataset is known to be dirty (...