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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
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Showing 361–390 of 3640 results
- AnthropicMediumSoftware EngineerAccount Balance with Expiring Grants
Design a data structure that tracks time-limited credit grants, prioritizes consuming grants that expire earliest, and efficiently manages expired funds.
Coding & AlgorithmsOnsiteHeapGreedyDesign - AnthropicMediumSoftware EngineerAnswer AI Safety Behavioral Prompts
This question evaluates behavioral and leadership competencies for a software engineering role, including alignment with organizational values, ethical judgment on AI safety, communication, mentorship, and influence on project and product decisions within the Behavioral & Leadership domain.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerAnswer Culture and Project Questions
This question evaluates a software engineer's behavioral competencies—ownership, judgment, communication, and values alignment—by prompting story-driven examples about past projects, difficult tradeoffs, and motivation for joining an AI safety–oriented research organization.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerAnswer culture-fit reflection questions
This question assesses a candidate's ability to demonstrate intellectual humility, accountability, and the capacity for self-directed growth in high-stakes technical environments.
Behavioral & LeadershipOnsiteAccountabilitySelf-AwarenessGrowth-Mindset - AnthropicMediumSoftware EngineerAnswer general fit and AI safety questions
Answer general fit and AI safety questions evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerApply bitwise tricks for performance
This question evaluates proficiency with bitwise operations, branchless programming, low-level performance optimizations, and microarchitectural reasoning about pipeline stalls, instruction-level parallelism, and cache behavior.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerBanking System Simulation
This question evaluates a candidate's ability to design a stateful, multi-level simulation system that processes a time-ordered stream of operations. It tests object-oriented design, incremental complexity management, and handling of deferred effects like scheduled cashback credits. Such object-modeling questions are commonly used in coding interviews to assess practical application of data structures under evolving requirements.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerBatch Image Resize and Rotate with Pillow: Exact Dimensions, Parallelism, Bad Files
A three-part Python image processing exercise: resize and rotate images with Pillow while predicting the exact printed dimensions, speed up a large batch with multiprocessing and a staged pipeline, then keep the batch running through corrupt, oversized and unsupported files. It tests API precision, parallelism and robustness.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerBatch-Apply Pillow Image Transforms, Then Parallelize: Processes vs Threads
A Python coding exercise that applies a given sequence of Pillow transforms to a folder of cat images and then asks you to cut the total processing time. It tests clean per-image code, reasoning about CPU-bound work and the GIL, choosing between processes and threads, and sizing a worker pool.
Software Engineering FundamentalsOnsite - AnthropicMediumMachine Learning EngineerBrainstorm How to Keep an AI Model Aligned With Its Intended Goals
Anthropic Fellows final-round practice: a 15-minute open discussion on defining, detecting and training against misalignment and misuse, ending with one falsifiable experiment.
Machine LearningOnsiteAnthropic FellowsAI Safety Fellowshipai-safety - AnthropicHardSoftware EngineerBuild a Progressive Banking Ledger
Design and implement an in-memory, timestamped banking ledger supporting atomic transfers, cashback, scheduled payments, account merges with alias resolution, and historical balance lookups.
Coding & AlgorithmsOnsitedesignheapbinary-search - AnthropicHardSoftware EngineerBuild a Progressive Cloud Storage System
Design and implement an in-memory cloud storage engine supporting user quotas, file operations, compression/restoration semantics, and glob-based search.
Coding & AlgorithmsOnsiteData StructuresSystem DesignOOP - AnthropicHardSoftware EngineerBuild a Progressive Employee Tracker
Design an in-memory attendance and payroll tracking system that manages shift lifecycles, deferred rate promotions, overlapping bonus windows, and duration rankings.
Coding & AlgorithmsOnsiteIntervalsBinary SearchObject-Oriented Design - AnthropicMediumSoftware EngineerBuild a Resize-and-Rotate Image Pipeline with Multiprocessing
Design a Pillow resize-and-rotate pipeline with explicit transform semantics, bounded multiprocessing, per-image failures, and safe output publication.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerBuild a least-recently-used cache
This problem tests your ability to implement an efficient LRU cache using a combination of a hash map and a doubly linked list to achieve constant-time operations.
Coding & AlgorithmsOnsiteData StructuresHash MapLinked List - AnthropicHardSoftware EngineerCalculate Streaming Token Usage Costs
Implement a robust token usage billing manager that accumulates streaming chunk deltas and non-streaming totals, enforces strict schema and sanity checks, and avoids floating-point precision loss.
Coding & AlgorithmsOnsiteAlgorithmsData StructuresSystem Design - AnthropicMediumSoftware EngineerCompare Threads and Processes for Image Processing
Tests operating system concurrency fundamentals, memory ownership models, IPC serialization overhead, and empirical benchmarking strategies for CPU-bound image processing pipelines.
Software Engineering FundamentalsOnsiteconcurrencyoperating-systemsperformance - AnthropicHardSoftware EngineerCompute Exclusive Time from Stack Events
Compute aggregate exclusive execution time for each function from nested start and end events, including recursive calls. Use a stack over a validated single-threaded trace, apply half-open time intervals, and return deterministic sorted results.
Coding & AlgorithmsOnsite - AnthropicHardSoftware EngineerCompute a Global Mode Across Distributed Partitions
Compute an exact distributed mode with local frequency combining, key-based reducers, global winner selection, communication accounting, and skew-aware recovery.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerCompute an Exact Distributed Median with Limited Communication
Compute an exact distributed median through global rank selection and count reductions, accounting for integer range, local search work, communication rounds, and even-size semantics.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerConvert Sampled Call Stacks into Start and End Events
Convert sampled call stacks to inferred start/end events using ordered common prefixes, recursive frames, explicit final-open behavior, and last-N history limitations.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerConvert Sampled Call Stacks into Timestamped Function Start and End Events
Convert a sampling profiler's timestamped call stacks into function start and end events for a trace viewer, explain why ends are emitted innermost first and starts outermost first, then redesign the converter for an unbounded stream. It tests stack diffing, recursion handling and streaming state.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerConvert Stack Samples into Trace Events
This problem tests your ability to manipulate tree-like path structures and manage state transitions using a stack, specifically focusing on efficiently calculating diffs between consecutive call stacks.
Coding & AlgorithmsOnsiteArraysStackStrings - AnthropicMediumMachine Learning EngineerConvert State Stream to Events
This question tests the ability to process a stream of state changes, group consecutive identical values into distinct event intervals, and filter these events based on duration.
Coding & AlgorithmsOnsiteArraysData ProcessingAlgorithms - AnthropicHardSoftware EngineerDebug Python LRU Cache-Key Construction
Implement and debug a thread-safe, bounded LRU memoization decorator that generates canonical cache keys across equivalent argument patterns, distinguishes conflicting types, and avoids caching exceptions.
Software Engineering FundamentalsOnsitepythonconcurrencycaching - AnthropicHardSoftware EngineerDebug Tokenization and Detokenization
Implement and debug a prefix-based tokenizer and detokenizer class, ensuring deterministic longest-match greedy tokenization, strict vocabulary validation, explicit error handling for unencodable characters, and guaranteed round-trip fidelity.
Software Engineering FundamentalsOnsitestring-algorithmstriesoftware-engineering - AnthropicHardMachine Learning EngineerDemonstrate culture fit and leadership
This question evaluates interpersonal and leadership competencies for a Machine Learning Engineer role, including cultural adaptability, trust-building, stakeholder alignment, cross-cultural communication, inclusion, delivering and receiving difficult feedback, and validating decisions with guardrails or safety checks.
Behavioral & LeadershipOnsite - AnthropicHardMachine Learning EngineerDeploy a Large Model to GPU Workers
Design a high-throughput, fault-tolerant artifact distribution system to deploy a 500 GB large language model across thousands of GPU worker nodes under strict time and bandwidth constraints.
System DesignOnsiteML InfrastructureDistributed SystemsNetworking - AnthropicMediumSoftware EngineerDescribe a Python design-and-coding approach in Colab
This question evaluates a candidate's ability to design and implement a Python-based solution within a cloud-hosted notebook environment, covering requirements elicitation, component and data-structure selection, modularization, testing, dependency and environment management, and basic performance analysis.
System DesignOnsite - AnthropicMediumSoftware EngineerDescribe a Strongly Held View That Proved Wrong
Tests intellectual humility, technical judgment, and the ability to pivot based on disconfirming evidence while taking full accountability for downstream impacts.
Behavioral & LeadershipOnsiteBehavioralIntellectual HumilityEngineering Judgment
Anthropic