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System Design 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 121–150 of 1311 results

  • AnthropicMediumSoftware Engineer
    Design a Team SQL Workbench with Snapshots and Async Runs

    Design a multi-user SQL workbench where analysts co-edit drafts, freeze immutable snapshots, and launch long-running warehouse queries whose results stay traceable to their exact inputs. Tests concurrency control, immutability boundaries, and reliable async execution.

    System DesignOnsitecollaborationversioningasync-jobs
  • AnthropicMediumSoftware Engineer
    Design a Telemetry Pipeline That Handles Inconsistent Metric Names from Old Clients

    Design a telemetry pipeline that ingests metrics from a large fleet of deployed clients, then handle legacy clients that cannot be updated and report the same metric under inconsistent names. It tests durable ingestion, stream processing and storage design, canonical metric catalogs, version-scoped name mapping and schema evolution.

    System DesignOnsite
  • AnthropicHardSoftware Engineer
    Design a Translation API That Batches Requests on a Fixed Clock

    Design a hosted translation API where a GPU worker runs one batch of pending requests every fixed round, and the candidate must derive throughput, batch-closing policy, and failure handling from that one constraint.

    System DesignOnsitesystem-designbatchingcapacity-planning
  • AnthropicHardSoftware Engineer
    Design a concurrent web crawler

    An Anthropic system design question: design and implement a concurrent web crawler, from a single-threaded baseline to manual threads, a thread pool and asyncio. It covers the URL frontier, deduplication across workers and redirects, robots.txt and per-host politeness, Retry-After backoff, completion detection, memory sizing, testing and monitoring.

    System DesignTechnical Screen
  • AnthropicMediumSoftware Engineer
    Design a distributed web crawler

    This question tests the ability to design a scalable, fault-tolerant distributed web crawler that handles URL management, distributed coordination, and domain politeness.

    System DesignTechnical ScreenDistributed SystemsScalabilityCaching
  • AnthropicMediumSoftware Engineer
    Design a one-to-one chat system

    This problem tests your ability to design a scalable, real-time one-to-one messaging system by addressing requirements for message ordering, delivery guarantees, and user presence.

    System DesignTechnical ScreenWebSocketsMessagingScalability
  • AnthropicHardSoftware Engineer
    Design a prompt playground

    This question evaluates a candidate's competency in large-scale system design, real-time streaming and prompt execution, multi-tenant data modeling, versioning and collaboration workflows, security and privacy controls, observability and cost tracking, and abuse prevention.

    System DesignOnsite
  • AnthropicMediumSoftware Engineer
    Design a prompt-sharing platform

    This question assesses the ability to design a scalable content-sharing platform, focusing on data modeling, efficient retrieval of user-generated prompts, and the handling of concurrent access and permissions.

    System DesignTechnical ScreenAPI DesignData ModelingScalability
  • AnthropicHardMachine Learning Engineer
    Design a scalable MapReduce pipeline

    Design a scalable MapReduce pipeline 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
  • AnthropicHardSoftware Engineer
    Design a scalable network I/O service

    This question evaluates a candidate's ability to design a scalable, highly available network I/O backend, testing competencies in distributed systems, storage architecture, CDN and caching integration, API and data model design, capacity planning, failure handling, observability, and security.

    System DesignTechnical Screen
  • AnthropicHardMachine Learning Engineer
    Design a scalable service and model performance

    This question evaluates a candidate's ability in large-scale distributed system design, performance modeling, capacity planning, and operational reliability for latency-sensitive, multi-region key-value services.

    System DesignOnsite
  • AnthropicHardSoftware Engineer
    Design a scalable, reliable system

    The prompt evaluates competence in large-scale distributed system design, covering storage architecture, consistency and replication strategies, caching, APIs and data models, operational reliability, security, and cost/capacity planning.

    System DesignTechnical Screen
  • AnthropicHardSoftware Engineer
    Design an LLM Prompt Playground: Schema, Large Prompts, Sharing and Tiny Edits

    A system design interview to build an LLM prompt playground where users write, run, save and share prompts, starting from the database schema. Follow-ups probe storing very large prompts, designing sharing, and handling frequent one- or two-character edits to a large prompt without wasting storage.

    System DesignOnsite
  • AnthropicHardSoftware Engineer
    Design an LLM Request Batcher When Every Batch Costs a Fixed Time

    Design the serving path for a code-completion model whose accelerators run requests in batches. The interviewer says one batch always takes a fixed 250 ms. Tests batching policy, capacity math, latency budgets, routing results back to callers, failure handling, and questioning the fixed-latency assumption.

    System DesignOnsitellm-servingbatchingqueueing
  • AnthropicHardSoftware Engineer
    Design distributed median and mode

    This question evaluates skills in distributed systems and large-scale analytics, covering data partitioning, streaming and sliding-window processing, quantile and heavy-hitter summarization, fault tolerance, and trade-off analysis for time, space, and network I/O.

    System DesignOnsite
  • AnthropicHardSoftware Engineer
    Design guardrails and fallback for LLM reliability

    Design an end-to-end safety and reliability middleware layer for a production LLM service, focusing on low-latency input/output guardrails, early streaming interception, multi-tier fallback strategies, and observability.

    System DesignOnsiteLLMSafetyStreaming Architecture
  • AnthropicHardSoftware Engineer
    Design production-ready dedup service

    This question evaluates system design and distributed storage competencies, focusing on scalable file deduplication, content-defined chunking, metadata and index design, multi-tenant architectures, and operational reliability across regions.

    System DesignTechnical Screen
  • AnthropicMediumSoftware Engineer
    Distribute 500 GB of Model Weights to 1,000 GPU Workers: Lower Bound and Design

    Copy 500 GB of model weights to 100 to 1,000 GPU workers whose 10 Gbps links are shared between upload and download. Derive the lower bound on distribution time, evolve a naive fan-out into a chunked peer-to-peer design, and handle stragglers, failures and cutover. It tests bandwidth reasoning and large-scale distribution design.

    System DesignOnsite
  • AnthropicHardSoftware Engineer
    Find a Distributed Mode Efficiently

    Design an exact distributed mode-finding algorithm across partitioned workers that minimizes network I/O, prevents hotspotting, handles deterministic tie-breaking, and contrasts with approximate streaming sketches.

    System DesignOnsitedistributed-systemssystem-designalgorithms
  • AnthropicHardSoftware Engineer
    Guide and override compiler optimizations

    This question evaluates a candidate's competency in low-level performance engineering and compiler optimization techniques—covering pragmas, intrinsics, manual code transformations, profiling and correctness verification—within the System Design and compiler-aware optimization domain.

    System DesignOnsite
  • AnthropicMediumSoftware Engineer
    How to stream a large file to 1000 hosts fastest

    Design a high-throughput distribution system to broadcast a large file (e.g., 100 GB model checkpoint) to 1,000 cluster hosts in minimum time, analyzing network bottlenecks and replication topologies.

    System DesignOnsitedistributed-systemssystem-designnetworking
  • AnthropicMediumSoftware Engineer
    How would you scale batch image pipelines?

    This problem evaluates your ability to design a distributed, fault-tolerant batch processing system for high-throughput image transformation tasks.

    System DesignTechnical ScreenDistributed SystemsScalabilityBatch Processing
  • AnthropicHardSoftware Engineer
    Identify and mitigate deduplication program risks

    This question evaluates understanding of system design and practical engineering competencies required for building resilient file deduplication tools, covering filesystem semantics, error handling, hashing and collision considerations, concurrency, performance bottlenecks, cross-platform interoperability, and safety trade-offs.

    System DesignTechnical Screen
  • AnthropicMediumMachine Learning Engineer
    Optimize MapReduce performance

    This question evaluates understanding of the MapReduce programming model and distributed batch processing at scale. It tests practical knowledge of parallel efficiency, network bottleneck analysis, and optimization techniques like combiners, partitioning, and speculative execution — core competencies assessed in machine learning and data engineering roles.

    System DesignTechnical Screen
  • AnthropicHardSoftware Engineer
    Optimize a compute kernel with a simulator

    This question evaluates performance engineering and low-level kernel optimization competencies, including profiling, data-layout and instruction-level techniques, correctness verification, and benchmark-driven measurement within the System Design domain.

    System DesignOnsite
  • AnthropicMediumSoftware Engineer
    Review a Batched GPU Inference API Design Doc: Flaws, Throughput, Mixed-Model GPUs

    Review a design document for a batched GPU inference API and find its flaws in load balancing, batching, caching, retries and admission control. Then compare theoretical and achievable throughput at 100 ms per batch and 10,000 QPS, and schedule a large and a small model on one 8-GPU pool.

    System DesignOnsite
  • AnthropicHardSoftware Engineer
    Scale crawler with thread pool

    This question evaluates system design and concurrent programming competencies, focusing on bounded thread-pool architecture, thread-safe frontier and deduplication structures, per-host politeness and in-flight limits, reliability mechanisms (timeouts, retries, backoff), and graceful shutdown and termination semantics.

    System DesignTechnical Screen
  • AnthropicHardSoftware Engineer
    Schedule instructions on a VLIW pipeline

    This question evaluates proficiency in VLIW instruction scheduling, pipeline hazard analysis (RAW/WAR/WAW), register-pressure management, and software-pipelining for loop kernels within the System Design domain of computer architecture and compiler backends.

    System DesignOnsite
  • AnthropicMediumSoftware Engineer
    System Design: Pushing a Multi-Terabyte Snapshot to Thousands of Nodes

    Figure out the theoretical floor on how fast a large search-index snapshot can reach every node in a fleet given each machine's shared upload/download bandwidth, then design a chunked, peer-assisted distribution scheme that approaches that floor and copes with stragglers and failures. Tests bandwidth reasoning and evolving a design from a naive baseline.

    System DesignOnsitesystem-designnetworkingdistributed-systems
  • AnyscaleMediumSoftware Engineer
    Design a Service That Sends a JSON Payload to a URL at a Scheduled Time

    Design a service that accepts JSON requests containing a target URL, a UTC timestamp and a payload, stores them durably, and sends each payload to its URL at the scheduled time. It tests finding due work at scale, delivery guarantees and retries, isolation from slow endpoints, outbound-request security and failure recovery.

    System DesignOnsite