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Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
- 9403
- Questions
- 546
- Companies
- 11
- Topics
- 8
- Languages
Showing 2971–3000 of 4616 results
- OpenAIMediumSoftware EngineerDesign a distributed crossword fill solver
This problem tests your ability to design a scalable, distributed architecture capable of solving large-scale constraint satisfaction problems (crossword filling) across a vast vocabulary.
System DesignTechnical ScreenDistributed SystemsConstraint SatisfactionBacktracking - OpenAIHardData ScientistDesign a free-month experiment
This question evaluates experimental design, causal inference, metric selection, bias mitigation, ROI estimation, and stakeholder communication skills within the Analytics & Experimentation domain for a Data Scientist role.
Analytics & ExperimentationTechnical Screen - OpenAIHardSoftware EngineerDesign a fullstack app with frontend focus
Design a fullstack app with frontend focus evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - OpenAIHardMachine Learning EngineerDesign a low-latency RAG system
This question evaluates ML system design skills, specifically the ability to architect retrieval-augmented generation pipelines under strict latency, cost, and multi-tenancy constraints. It tests how candidates reason about vector search, re-ranking, and LLM integration at production scale — a core competency for senior machine learning engineering roles.
ML System DesignTechnical Screen - OpenAIMediumSoftware EngineerDesign a metrics monitoring system, going deep on one or two components
A system design question about a metrics monitoring system that collects time series from services and hosts, stores them, serves dashboard queries and raises alerts. After a brief end-to-end sketch, the candidate goes deep on one or two areas, such as time-series storage, label cardinality, downsampling or reliable alert evaluation.
System DesignTechnical Screen - OpenAIHardSoftware EngineerDesign a minimal ChatGPT with presets
This question evaluates a candidate's competency in designing multi-tenant conversational AI services with reusable, versioned presets, covering API design, data modeling, session state and context-window management, scalability, multi-tenant isolation, privacy, and observability.
System DesignTechnical Screen - OpenAIMediumSoftware EngineerDesign a multi-device calendar application
This question tests the ability to design a distributed calendar system focusing on synchronization, conflict resolution for overlapping time slots, and efficient storage of recurring events.
System DesignTechnical ScreenDistributed SystemsData ModelingSync - OpenAIHardSoftware EngineerDesign a multi-tenant CI/CD platform
An OpenAI software-engineering system-design screen asking you to design a scalable, multi-tenant CI/CD platform. It spans Git/event intake, YAML workflow parsing into a job DAG, fair scheduling and runner isolation, live log and status streaming, per-tenant quotas and billing, observability, audit logging, disaster recovery, and zero-downtime deploys.
System DesignTechnical Screen - OpenAIHardSoftware EngineerDesign a multi-tenant Slack-like messenger
This question evaluates skills in large-scale distributed systems architecture, real-time messaging and presence, data modeling for multi-tenant platforms, security and compliance features, and operational concerns like observability and cost efficiency.
System DesignTechnical Screen - OpenAIHardSoftware EngineerDesign a payment system with holds and batching
This question tests the ability to design a high-consistency payment processing system that handles asynchronous state transitions, authorization holds, and batch settlement workflows.
System DesignTechnical ScreenPaymentsIdempotencyDistributed Systems - OpenAIMediumSoftware EngineerDesign a persistent key-value store
This question evaluates a candidate's ability to design persistent storage and in-memory data structures, covering serialization of arbitrary values, medium/interface design for byte-level persistence, crash-consistent flushing, error handling, and performance and complexity analysis.
Coding & AlgorithmsTechnical Screen - OpenAIHardMachine Learning EngineerDesign a production RAG system
An OpenAI ML system design interview question (MLE technical screen): design a production, multi-tenant retrieval-augmented generation (RAG) system for enterprise document QA. The model answer covers ingestion and chunking, embedding selection, ANN/vector indexing (HNSW vs IVF-PQ), hybrid retrieval and cross-encoder re-ranking, prompt orchestration with citation grounding, hallucination mitigation, caching and freshness, multilingual and PII/safety handling, scalability and disaster recovery, observability and offline/online evaluation, an API and data schema, cost controls, and a phased rollout. It tests trade-off reasoning across recall, latency, cost, and compliance.
ML System DesignTechnical Screen - OpenAIHardSoftware EngineerDesign a response-ranking ML system
Design a response-ranking ML system evaluates ML product requirements, data/labeling, modeling, serving architecture, evaluation, monitoring, and trade-offs in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
ML System DesignTechnical Screen - OpenAIHardSoftware EngineerDesign a scalable payment system
Design a scalable payment system evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - OpenAIMediumSoftware EngineerDesign a social network with snapshots
This problem tests your ability to design a memory-efficient versioned graph structure that supports efficient edge retrieval at arbitrary points in time.
Software Engineering FundamentalsTechnical ScreenGraphData StructuresVersioning - OpenAIHardSoftware EngineerDesign a team chat system
This question tests the ability to design a scalable, low-latency, real-time messaging system, focusing on message ordering, delivery guarantees, and high-concurrency state management.
System DesignTechnical ScreenScalabilityWebSocketsDistributed Systems - OpenAIHardSoftware EngineerDesign an AI playground editor
This problem tests your ability to design a scalable, low-latency document editor that integrates real-time AI streaming responses into a persistent, collaborative text environment.
System DesignTechnical ScreenReal-timeStreamingAPI Design - OpenAIMediumMachine Learning EngineerDesign an Editable Text Buffer
This problem tests your ability to design an efficient data structure for text manipulation while implementing undo/redo history and a dynamic prefix-based autocomplete feature.
Coding & AlgorithmsTechnical ScreenData StructuresTrieUndo-Redo - OpenAIHardMachine Learning EngineerDesign an In-Memory Key-Value Cache
Implement a thread-safe in-memory key-value cache supporting capacity bounds, LRU eviction, and per-key time-to-live (TTL) expiration.
Software Engineering FundamentalsTechnical ScreenData StructuresConcurrencyLRU Cache - OpenAIMediumSoftware EngineerDesign an Instagram-like Feed System
This question assesses the ability to architect a high-scale feed system by balancing pre-computation (push model) versus on-demand computation (pull model) to minimize latency for social media users.
System DesignTechnical ScreenScalabilityCachingData Modeling - OpenAIHardMachine Learning EngineerDesign an ML search system
This question evaluates system-design and information-retrieval competencies for machine-learning-powered enterprise document search, covering ingestion and indexing pipelines, hybrid lexical and semantic retrieval, feature generation and ranking, multi-tenant access control, and security/compliance.
ML System DesignTechnical Screen - OpenAIHardMachine Learning EngineerDesign an ML search system with RAG
Design an ML search system with RAG evaluates ML product requirements, data/labeling, modeling, serving architecture, evaluation, monitoring, and trade-offs in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
ML System DesignTechnical Screen - OpenAIMediumMachine Learning EngineerDesign an OOD detection system
This question tests the ability to design an end-to-end system for detecting out-of-distribution (OOD) data in production LLMs to ensure reliability and safety.
ML System DesignTechnical ScreenLLMMLOpsOOD - OpenAIMediumSoftware EngineerDesign an Offline Merchant Payment System with Reconciliation
This question tests your ability to design a distributed payment architecture that supports asynchronous transactions and reliable reconciliation between offline Point-of-Sale (POS) terminals and a centralized ledger.
System DesignTechnical ScreenDistributed SystemsEventual ConsistencyPayment Gateway - OpenAIHardSoftware EngineerDesign an On-Demand Cloud Notebook Service for ML Engineers
Design a platform that gives ML engineers on-demand, GPU-backed notebook workspaces they can create, connect to, pause, and resume, covering lifecycle and API design, provisioning latency, persistent storage, and idle-cost control.
System DesignTechnical Screensystem-designinfrastructurescalability - OpenAIHardSoftware EngineerDesign an Online Devbox Service for On-Demand Cloud Development Environments
System design question about an online devbox service that gives engineers cloud development environments they can create, connect to, stop and resume. It tests lifecycle and API design, fast provisioning, persistent workspace storage, connection routing, isolation of user code, idle cost control and failure handling.
System DesignTechnical Screen - OpenAIHardSoftware EngineerDesign an Online Development Box
Design an online devbox with authenticated workspace access, isolated code execution, persistent project files, reliable stop/resume, and controlled startup costs.
System DesignTechnical Screen - OpenAIHardSoftware EngineerDesign an enterprise RAG assistant for internal docs
This question evaluates expertise in designing and training Retrieval-Augmented Generation (RAG) systems, including retriever, evaluator (reranker/verifier/filter), and generator components, with emphasis on model architecture choices, training objectives, data preparation under privacy and document-permission constraints, and evaluation strategies for grounded answers with citations. It is commonly asked to probe advanced ML system design and operationalization skills for mitigating hallucination, stale or conflicting sources, and long-document retrieval; the category is ML System Design and the level is practical application-focused with detailed modeling and training considerations.
ML System DesignTechnical Screen - OpenAIHardSoftware EngineerDesign an in-memory database
This problem tests the ability to architect a high-performance, in-memory key-value store, focusing on concurrency control, data structures, and durability guarantees.
System DesignTechnical ScreenConcurrencyData StructuresCaching - OpenAIHardSoftware EngineerDesign an in-memory key-value database
Design an in-memory key-value database evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen
OpenAI