Senior+ 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 a "Future Best-Sellers" Prediction and Recommendation System
Design a "Future Best-Sellers" Prediction and Recommendation System An e-commerce platform wants a new feature on its category pages. A user selects a...
Design Comment Prediction Ranking System
This question evaluates proficiency in end-to-end machine learning system design for predicting user engagement, specifically the probability of a use...
Design Video Intelligence for Investigations
This question evaluates a candidate's competency in designing scalable, multimodal video intelligence systems that integrate machine learning, informa...
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 payment fraud detection
Design a machine learning system for fraud detection in an online payment platform. The system should score transactions before or shortly after autho...
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 video recommendation system
Scenario You are designing an ML-driven video recommendation product (home feed + “up next”) for a consumer app. The interviewer focuses heavily on in...
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...
Explain an ML Project from Model Development Through Deployment
Choose one machine-learning project from your experience and explain it from problem definition through online deployment. Focus on how you selected t...
Design a Family-Friendly Listing Classifier
Design a machine learning system for a short-term rental marketplace that classifies whether a property listing is suitable for families. Users should...
Present a Marketplace ML Project Deep Dive
In a Machine Learning Engineer interview for a pricing, marketplace, or growth team, present a recent representative ML project. Your deep dive should...
Design a Synchronous Text Classification API
Design a Synchronous Text Classification API A trained machine-learning model classifies text. Design the system that exposes this model through synch...
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...
Improve Trust in a RAG System
You own an enterprise retrieval-augmented generation system used for high-stakes document question answering, such as mortgage underwriting, legal rev...
Design Detection Systems for Risk and Safety
This question evaluates a machine learning engineer's competence in designing end-to-end detection systems for risk and safety, covering skills in dat...
Design AI-Powered Document Search
This question evaluates system-design and machine-learning engineering skills for building a scalable AI-enabled document ingestion pipeline, covering...
Design an unsafe content detection system
This question evaluates a candidate's competency in end-to-end machine learning system design for unsafe user-generated content detection, covering mu...
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...
Improve LLM reasoning for a domain task
This question evaluates competency in end-to-end LLM system design for improving multi-step reasoning, including task specification, data construction...
Design Harmful Content Detection
This question evaluates a candidate's ability to design scalable, robust machine learning systems for multimodal content moderation, encompassing comp...