Design a Gang-Scheduled GPU Inference Pool
Design an inference request path with explicit latency accounting and one-GPU or all-GPU batches that each complete in 100 milliseconds.
Open practiceAnthropic interview practice
Practice from 26 Anthropic-tagged public coding problems, organized only by the stage, topic, difficulty, and recency metadata FastPrep can verify. The broader public catalog also includes 11 system-design exercises, 4 project-coding exercises.
OA practice path
Build a timed implementation rhythm from prompt to edge cases. Problems are ranked by repeated public catalog sightings.
18 Anthropic-tagged Online Assessment problems available.
| Company | Problem | Difficulty | Public evidence | Action |
|---|---|---|---|---|
ANAnthropic | In-Memory Database with Backup and RestoreDesignHash Table | Hard | 13 public reportsLast reported May 2026 | Practice |
ANAnthropic | Banking System, Part 1: Accounts and TransfersDesignHash Table | Easy | 11 public reportsLast reported Oct 2026 | Practice |
ANAnthropic | Banking System, Part 2: Top SpendersDesignHash Table | Medium | 10 public reportsLast reported Jul 2026 | Practice |
ANAnthropic | Banking System, Part 3: Scheduled PaymentsDesignHash Table | Hard | 10 public reportsLast reported Jul 2026 | Practice |
ANAnthropic | Banking System, Part 4: Merging and Balance HistoryDesignHash Table | Hard | 10 public reportsLast reported Jul 2026 | Practice |
ANAnthropic | Cloud Storage SystemDesignHash Table | Medium | 9 public reportsLast reported Aug 2026 | Practice |
ANAnthropic | In-Memory Database Historical LookupHash TableDatabase | Hard | 6 public reportsLast reported Nov 2025 | Practice |
ANAnthropic | Worker Management, Part 1: Office RegistrationHash TableDesign | Easy | 4 public reportsLast reported May 2026 | Practice |
ANAnthropic | Worker Management, Part 2: Top WorkersHash TableSorting | Medium | 4 public reportsLast reported May 2026 | Practice |
ANAnthropic | Worker Management, Part 3: Promotions and SalaryHash TableIntervals | Hard | 4 public reportsLast reported May 2026 | Practice |
ANAnthropic | Worker Management, Part 4: Double-Paid IntervalsHash TableIntervals | Hard | 4 public reportsLast reported May 2026 | Practice |
ANAnthropic | Repair the Bootloader ProgramArraySimulation | Medium | 3 public reportsLast reported Sep 2026 | Practice |
ANAnthropic | Cloud Storage Compression and DecompressionHash TableSorting | Hard | 3 public reportsLast reported Feb 2026 | Practice |
ANAnthropic | Banking Pending Transfer AcceptanceHash TableDesign | Medium | 2 public reportsLast reported Jul 2024 | Practice |
ANAnthropic | Task Management SystemDesignHash Table | Hard | 1 public reportLast reported Aug 2026 | Practice |
ANAnthropic | Normalize a DNS Domain NameString | Easy | 1 public reportLast reported May 2026 | Practice |
ANAnthropic | Cloud Storage File VersioningHash TableSorting | Medium | 1 public reportLast reported Apr 2024 | Practice |
ANAnthropic | Cloud Storage Prefix Trash and RestoreHash TableString | Hard | 1 public reportLast reported Apr 2024 | Practice |
Phone practice path
Practice solving while explaining assumptions, tradeoffs, and complexity. Problems are ranked by repeated public catalog sightings.
| Company | Problem | Difficulty | Public evidence | Action |
|---|---|---|---|---|
ANAnthropic | Convert Stack Samples to Trace EventsStackSimulation | Medium | 12 public reportsLast reported Sep 2026 | Practice |
ANAnthropic | Confirmed Profiling Events with First-Observed StartsArrayStack | Hard | 3 public reportsLast reported Sep 2026 | Practice |
ANAnthropic | Profiling Events from Consecutive Stack SamplesArrayStack | Hard | 3 public reportsLast reported Sep 2026 | Practice |
ANAnthropic | Find Duplicate File GroupsArrayString | Medium | 1 public reportLast reported Sep 2026 | Practice |
ANAnthropic | Crawl Same-Hostname URLs ConcurrentlyGraphBreadth-First Search | Medium | 1 public reportLast reported Sep 2026 | Practice |
Onsite practice path
Practice complete solutions and defend the choices behind them. Problems are ranked by repeated public catalog sightings.
| Company | Problem | Difficulty | Public evidence | Action |
|---|---|---|---|---|
ANAnthropic | Convert Stack Samples to Trace EventsStackSimulation | Medium | 12 public reportsLast reported Sep 2026 | Practice |
ANAnthropic | Confirmed Profiling Events with First-Observed StartsArrayStack | Hard | 3 public reportsLast reported Sep 2026 | Practice |
ANAnthropic | Profiling Events from Consecutive Stack SamplesArrayStack | Hard | 3 public reportsLast reported Sep 2026 | Practice |
ANAnthropic | Repair the Bootloader ProgramArraySimulation | Medium | 3 public reportsLast reported Sep 2026 | Practice |
ANAnthropic | Recover a Function-Call LRU Cache with a Write-Ahead LogDesignHash Table | Hard | 1 public reportLast reported Oct 2026 | Practice |
ANAnthropic | Trace Events from Stable Whole-Stack StatesArrayString | Medium | 1 public reportLast reported Oct 2026 | Practice |
ANAnthropic | Cache Shared Image Pipeline PrefixesArrayMatrix | Hard | 1 public reportLast reported Aug 2026 | Practice |
01 · Stage workflow
Combine algorithm work with public system-design and project-coding practice so preparation covers both narrow implementation and larger engineering decisions. Your invitation and recruiter guidance remain the source of truth.
Use the timing and format in your invitation as the source of truth. In practice, work without interruptions, budget time to read constraints, and reserve a final review window for boundary cases.
Treat the problem as a conversation. Clarify the contract, describe the approach before implementation, and keep narrating meaningful decisions while you code and test.
Use the catalog's onsite labels as practice context, not as a promise about a specific loop. Focus on collaborative problem solving: compare approaches, implement cleanly, and explain how the solution behaves at scale.
02 · Broader technical practice
These public Anthropic-tagged exercises cover additional technical formats. They are included only when a verified catalog record and a crawlable practice page both exist.
Design an inference request path with explicit latency accounting and one-GPU or all-GPU batches that each complete in 100 milliseconds.
Open practiceDesign a collaborative prompt experimentation product with immutable versions, reproducible runs, searchable results, and safe model-provider execution.
Open practiceImplement image resizing, choose a concurrency model, and process independent transformations concurrently.
Open practiceDesign a durable web messaging service for private two-person conversations, including conversation discovery, ordered storage, replayable delivery, replica-aware reads, burst handling, and offline recovery.
Open practiceSize and route online and offline inference across opaque GPU workers using measured capacity, batching, and explicit overload policy.
Open practiceServe versioned large models on shared accelerators with shard-aware scheduling, continuous batching, bounded admission, streaming recovery, stable experiments, and safe fallback or rollback.
Open practiceCompute an exact median across ten partitioned workers while balancing transmitted bytes against coordinated rounds.
Open practiceCompute one exact deterministic mode across ten partitioned workers while minimizing transmitted value/count data.
Open practiceDesign a deterministic control plane and data path that converge legacy telemetry-name variants onto canonical metrics without fuzzy matching.
Open practiceDesign a control plane that safely distributes large immutable model versions to serving fleets through staged rollout, verification, activation, and rollback.
Open practiceDesign a topology-independent peer-to-peer system that disseminates one large immutable model while respecting a shared per-node bandwidth limit.
Open practiceDebug the provided Extremely Randomized Trees implementation so it is correct and no longer suffers bugs that cause crashes or poor accuracy.
Open practiceImplement the request scheduler of an LLM inference engine, assigning prefill and decode work across progressively harder levels.
Open practiceScale and optimize an existing online ML service using end-to-end metrics, traces, logs, controlled releases, and explicit overload behavior.
Open practiceRepair a supplied agent, make it answer every question within two turns, then reduce the solution to one turn.
Open practice03 · Evidence boundary
It means practicing transferable implementation, testing, and technical reasoning with public catalog assets FastPrep tags to Anthropic. It does not mean FastPrep has access to the company's assessments or any private interview bank.
Repeated public sightings and last-reported dates can help you prioritize practice, but they cannot predict the questions, format, or platform in a specific interview.
04 · Plain answers
This page owns technical-practice intent for Anthropic. Hiring activity, timelines, and market signals remain on the separate hiring-insights page.
Yes, when the public catalog supports it. This page currently links 11 system-design exercises, 0 low-level-design exercises, and 4 project-coding exercises tagged to Anthropic. Empty formats are omitted rather than padded with generic recommendations.
No. FastPrep is an independent interview-preparation product and is not affiliated with Anthropic. The page uses FastPrep's public practice catalog and does not claim official, private, leaked, or proprietary employer questions.
Stage labels come from FastPrep's public problem metadata. A problem can carry more than one reported stage, and hiring processes can change by role, level, location, and date. Treat the labels as preparation context, not a guarantee.
Start with the stage named in your invitation or recruiter message. If no stage is known, use the largest available set to build general problem-solving fluency, then rehearse explanation and testing separately.
No. Public catalog counts, stage tags, and last-reported dates can help prioritize practice, but they cannot predict a specific interview's questions, sequence, timing, or platform.
Your next stage, made concrete
Start with the stage named in your invitation, then use public evidence as context—not as a promise of what you will be asked.
Open the practice set