Skip to content

Explore

Questions Companies Concepts Guides Sign in

How it works Questions Companies Concepts Guides Pricing Sample scorecard

Interview questions

Find a company or topic. Read the sources, then practice.

Coding study plans Companies Design mock

Loading the question library…

Practice system design interviews out loud with an AI interviewer, a shared whiteboard and a scorecard for your level.

How it works Questions Concepts Questions by company Comparisons Technologies Guides Cheat sheet Sample scorecard FAQ Use it as an app Sign in Pricing About and how we write Terms and guidelines Privacy Policy Contact

© 2026 SysRound. SysRound is an AI practice tool. The AI interviewer and the AI feedback can be wrong. Use it for your own practice, not to hire people.

Interview questions by company and topic | SysRound

Search questions

CompanyType a name, then choose a company from the suggestions.

Question type

Difficulty

TopicType a topic, then choose one from the suggestions.

11 questions

Showing 1–11

ML system designHard
Design a Multi-Tenant Enterprise RAG Assistant: Hybrid Retrieval, Reranking, ACLs
Companies: OpenAI
Embeddings & Vector Search · ML System Design · Retrieval-Augmented Generation
Last reported Sep 2026
Open workspace
ML system designHard
Design a Retrieval-Augmented Generation (RAG) system
Design a Retrieval-Augmented Generation (RAG) system that enhances large language model responses by retrieving relevant information from external knowledge sources, covering…
Companies: Atlassian, OpenAI, Scale AI
Embeddings & Vector Search · Retrieval-Augmented Generation
Last reported Jul 2026
Open workspace
ML system designHard
Design an ML search system

Companies: OpenAI

Embeddings & Vector Search · Search Relevance

Last reported Sep 2025

ML system designHard

Design a production RAG system

Companies: OpenAI

Embeddings & Vector Search · ML System Design · Retrieval-Augmented Generation

Last reported Aug 2025

ML system designHard

Design a low-latency RAG system

Companies: OpenAI

Embeddings & Vector Search · ML System Design · Retrieval-Augmented Generation

Last reported Jul 2025

Machine learningMedium

Assemble a RAG Pipeline From Provided Python Interfaces and Explain Retrieval

Companies: Visa

Embeddings & Vector Search · Retrieval-Augmented Generation

Machine learningEasy

Design and evaluate a RAG system

Companies: Amazon

Embeddings & Vector Search · Retrieval-Augmented Generation

Machine learningHard

Find companies similar to a given client

Companies: Google

Embeddings & Vector Search · Retrieval & Candidate Generation

Machine learningHard

How to deploy and tune multimodal models?

Companies: ByteDance

Embeddings & Vector Search · MLOps & Model Serving

Machine learningHard

Implement 1NN Embeddings and Forward Pass

Companies: Meta

Embeddings & Vector Search · ML Coding

Machine learningMedium

Retrieval-Augmented Generation Walkthrough: Indexing, Retrieval and Grounded Answers

Companies: Inpost

Embeddings & Vector Search · Retrieval-Augmented Generation