Openai Machine Learning Engineer ML System Design Interview Questions
Practice the exact questions companies are asking right now.
"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 RAG system with evaluation
Scenario You are asked to design a Retrieval-Augmented Generation (RAG) system that answers user questions using a private corpus (e.g., internal docs...
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 (...
Design a recommendation system end-to-end
Question Design a large-scale recommendation system (e.g., short videos or e-commerce items). Requirements - Personalized feed ranking for hundreds of...
Select high-quality math documents from crawls
Scenario You have a web crawler that collects raw HTML/PDF documents. You want to build a pipeline that identifies high-quality math documents suitabl...
Design and optimize a RAG system
Scenario You are building a Retrieval-Augmented Generation (RAG) system for question answering over an internal document corpus. Task Design the end-t...
Design a harmful video content moderation system
Question Design an end-to-end system to detect and moderate harmful videos on a large platform. Requirements - Detect multiple policy categories (viol...
Design an image/video near-duplicate detection system
Question Design a system to detect near-duplicate images/videos (e.g., reuploads, minor edits, different encodes) at large scale. Requirements - Suppo...
Design a chatbot fallback for unknown questions
Scenario You run a ChatGPT-like assistant. Users sometimes ask questions the model cannot answer reliably (unknown/uncertain/needs up-to-date facts). ...
Design an AWS fine-tuning platform for LLMs
Scenario You need to build a system that lets customers fine-tune their own large language model (LLM) on AWS. Task Design a managed platform where us...
Design a production RAG system
Design a Production RAG System for Enterprise Document QA Context You are designing a Retrieval-Augmented Generation (RAG) system to answer questions ...
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 low-latency RAG system
System Design: Production-Grade RAG for Customer Support (p99 ≤ 1.5 s) Goal Design a production-ready retrieval-augmented generation (RAG) system for ...
Design an enterprise RAG system
System Design: Retrieval-Augmented Generation (RAG) for Enterprise Context Design a production-grade, multi-tenant RAG platform for enterprise users. ...
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 an ML search system
Design an ML‑Powered Enterprise Document Search System Context You are designing a multi‑tenant enterprise search system that indexes documents from m...
Design LLM search handling long token inputs
You are asked to design an LLM-powered search system that lets users query a large corpus of documents (e.g., internal wikis, PDFs, logs, and web page...
Design enterprise RAG search system
Design an End-to-End Enterprise RAG Search System Background You are tasked with designing a Retrieval-Augmented Generation (RAG) search system for en...