Microsoft ML System Design Interview Questions
Practice the exact questions companies are asking right now.
"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 Chatbot Personalization Memory
Design a text-only personalization and memory system for an AI chatbot. The chatbot should use a user's previous conversations, stated preferences, an...
Design a Product Search System
Design a product search system for a large e-commerce marketplace. Users enter free-text queries such as wireless headphones, apply filters such as pr...
Design a RAG Ranking Pipeline
Design a retrieval-augmented generation pipeline for Microsoft Teams that helps an AI agent answer a user query by finding the most relevant applicati...
Design a RAG system with agentic tools
Design a Retrieval-Augmented Generation (RAG) question-answering system for an enterprise knowledge base. Requirements: - Users ask natural-language q...
Design a video VLM end-to-end
Prompt: Design a video vision-language model (VLM) from scratch You are asked to design an end-to-end system to build a video vision-language model th...
Design quality checks for spreadsheet LLM data
You are given a dataset for a spreadsheet assistant. Each example contains: 1. a natural-language prompt, 2. an Excel-style table or worksheet represe...
Explain Transformers and deploy an LLM safely
Answer the following LLM-focused questions. 1) Transformer basics - What problem does the Transformer architecture solve compared with RNNs? - Explain...
Design email ranking and summarization in Outlook
Scenario You are building ML features for an email client: 1) Debias email display order (inbox ranking) so users see the most relevant emails first w...
Calibrate LLM output to match Word formatting
Scenario You’re building an LLM-powered feature in a word processor (e.g., Microsoft Word) that generates content users can insert directly into a doc...
Optimize vector semantic search for an assistant
Scenario You own the vector semantic search layer for an AI assistant (e.g., Copilot). Users query across enterprise documents and/or product knowledg...
Infer user intent from typing in real time
Scenario You’re building an AI feature that observes a user’s typing stream in an editor/search box and predicts the user’s intent in real time. This ...
Design a RAG-based assistant service
Scenario You need to build a Retrieval-Augmented Generation (RAG) assistant for an enterprise product. It should answer questions using internal docum...