Openai Machine Learning Engineer ML System Design Interview Questions
Practice 17 real ML System Design interview questions for Machine Learning Engineer roles at Openai.
"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 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 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 ...
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 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...
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 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 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 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 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 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...
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
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...