Software Engineer ML System Design Interview Questions
Practice 117 real ML System Design interview questions for Software Engineer roles. From companies including Anthropic, OpenAI, Amazon, NVIDIA, Meta.
"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 Premium Product Recommendations
This question evaluates a candidate's ability to design an ML-powered recommendation system, testing competencies in personalization, data requirement...
Review an inference API design for scale
System Design Review: A Machine-Learning Inference API at Scale Background You are reviewing a teammate's design document for a production machine-lea...
Design a high-concurrency LLM inference service
This question evaluates a candidate's ability to design a high-concurrency LLM inference platform, assessing competencies in GPU utilization and memor...
Design a RAG-Based Agent System
This question evaluates a candidate's competency in designing end-to-end Retrieval-Augmented Generation (RAG) systems and LLM-based agents, covering r...
Design Hebbia Chat for SEC Filings
This question evaluates expertise in ML system design, specifically the ability to architect a multi-agent retrieval-augmented generation pipeline at ...
Design an LLM-based binary classifier
Design a Binary Text Classifier Using Only a Log-Probability Scoring Helper Context You are building a binary text classifier without fine-tuning. You...
Design a Hybrid Evaluation Platform
This question evaluates skills in designing scalable ML evaluation platforms, covering architecture, data modeling, human-in-the-loop workflows, LLM-b...
Design a low-latency ML inference API
System Design: Low-Latency ML Inference API (Real-Time) Context You are designing an in-region, synchronous ML inference API that sits on the critical...
Design a Credit Scoring Platform
This question evaluates competency in designing large-scale ML-driven systems, including system architecture, data ingestion and processing, model sco...
Design a Multimodal Training Data Pipeline
Design a backend system for collecting, filtering, and storing training data sent by many clients. Clients upload records that may include large media...
Design a content moderation platform
Design a large-scale content moderation system for a short-video platform. Users can upload videos, captions, comments, audio, and other metadata. The...
Design a chatbot (system design)
Question Design an AI chatbot system with a front-end focus, under the following hard constraints: 1. User messages and conversation history are store...
Design a Code Review Agent
Design an AI-powered code review agent that assists developers by reviewing pull requests and producing actionable feedback. The agent should be able ...
Design Pin recommendation system
Design Pinterest's Home Feed Recommendation System Problem Design an end-to-end recommendation system that powers the personalized home feed on Pinter...
Build and design a Mistral RAG agent
Design and Implement a Minimal LLM-Powered RAG Agent (Python, Mistral API) Context You are asked to build a minimal, but production-minded, retrieval-...
Design comment-likelihood prediction platform
Scenario You’re building an ML platform component that serves a model to predict the likelihood that a user will comment on a given post. The intervie...
Design a Static Audio Detection System
System Design: Static Audio Detection Pipeline Context Design an offline (non-live) audio detection system that processes static audio files (e.g., us...
How would you optimize large-scale training/inference?
This question evaluates a candidate's skills in ML system design, GPU/CUDA performance engineering, and distributed training and inference optimizatio...
Choose Fast or Cheap Models
You are building an AI-powered product and must choose between two inference options for each request: - Option A: higher cost per token, but lower la...
Design a RAG Ranking Pipeline
This question evaluates expertise in retrieval-augmented generation, information retrieval and ranking, indexing and offline data pipelines, model int...