Machine Learning Engineer ML System Design Interview Questions
Practice 194 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 chatbot over structured and unstructured data
This question evaluates a machine learning engineer's ability to design end-to-end systems that integrate structured and unstructured data, testing co...
Optimize LLM Training and Serving
This question evaluates hardware-aware ML systems engineering skills, specifically reasoning about memory-versus-compute bottlenecks and attention mat...
Design a Drop-off Spot Selector
This question evaluates expertise in ML-driven system design for safety-critical autonomous vehicle decisions, covering real-time decision-making, geo...
Design Streaming Speech and Multi-Model Chat Systems
Design Streaming Speech and Multi-Model Chat Systems Redesign a batch speech-transcription pipeline to process audio incrementally and support multipl...
Design Place Recommendation System
Design a machine learning system for a maps or local-discovery product that recommends places a user may want to visit. The system should provide pers...
Manage Context Windows in an Applied AI System
Manage Context Windows in an Applied AI System Design the context-building layer for an applied AI assistant. It must combine the current request, con...
Design Candidate Search And LLM Evaluation Tasks
Prepare for an MLE onsite with three themes: finding top candidates from a job description, reasoning about an unreliable deterministic comparator, an...
Design an app-store app recommendation system
This question evaluates a candidate's competency in end-to-end machine learning system design for recommender systems, covering personalization, candi...
Design a Game Recommendation System
This question evaluates mastery of designing scalable end-to-end machine learning recommendation systems, including candidate generation, multi-stage ...
Design a Revenue Ranking Platform
This question evaluates a machine learning engineer's competency in designing production-scale recommendation and ranking systems that balance revenue...
Design a fraud detection system
This question evaluates a candidate's competency in designing end-to-end fraud detection machine learning systems, covering real-time and batch featur...
Design a Multi-Agent Document Search and Visualization Product
Design a Multi-Agent Document Search and Visualization Product Design a document-analysis product that searches PDF content, extracts figures and tabl...
Design a Real-Time Sensor Intelligence System
Design an end-to-end real-time sensor intelligence system for a product team. Start from ambiguous product requirements and cover the full lifecycle: ...
Design a real-time recommendation system
You are asked to design a real-time recommendation system for a large-scale consumer product (for example, recommending items or content to users in a...
Design comment ranking
This question evaluates competency in designing large-scale machine learning ranking systems, testing skills such as candidate generation, label and t...
Design multi-GPU matrix multiplication
Multi-GPU MatMul (2 GPUs): Design and Implementation You are given two GPUs connected via NVLink or PCIe. You must compute C = A × B where: - A is sha...
Design a short-video recommender for short-term interest
This question evaluates a candidate's understanding of real-time personalized recommendation systems, with emphasis on session-based short-term intere...
Design User Embedding Semantic Search
Design a user-embedding-based two-stage semantic retrieval and ranking system for a short-term rental marketplace. The goal is to retrieve and rank pr...
Design an OOD detection system
This question evaluates a candidate's competency in ML system design, specifically out-of-distribution detection, production monitoring, interpretabil...
Design a news feed ranking system
This question evaluates a candidate's ability to architect a scalable, low-latency personalized news feed recommendation system, assessing competencie...