practice a little every day, paws crossed ♡
Software Engineer 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 751–780 of 5874 results
- AnthropicMediumSoftware EngineerGenerate Function Profiling Events from Stack Samples
Generate function start and end events from timestamped stack samples, including independently debounced frames across consecutive samples. Address transient appearances and absences, changing stack suffixes, shared timestamps, deep stacks, end-of-input behavior, complexity, and online processing.
Coding & AlgorithmsTechnical Screen - AnthropicMediumSoftware EngineerGenerate outputs for images and pipelines
This question evaluates algorithmic and systems engineering skills related to batch image processing, parallelization, I/O versus CPU trade-offs, and deterministic output association within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - AnthropicMediumSoftware EngineerGive a Credible Why-This-Organization Answer
Build a credible answer to a recruiter asking why a mission-driven AI organization and role matter to you. The framework connects public mission, truthful technical evidence, career timing, transferable skills, knowledge gaps, and a focused question without relying on prestige or invented experience.
Behavioral & LeadershipHR Screen - AnthropicHardSoftware EngineerGuide 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 EngineerHiring-Manager Behavioral Round: Impact, Conflict, Cross-Functional Work, and Influencing Without Authority
Tests a candidate's ability to drive technical initiatives across teams, navigate cross-functional disagreements, and exert leadership without formal management authority.
Behavioral & LeadershipOnsiteBehavioralLeadershipCross-Functional - AnthropicHardSoftware EngineerHow do you design an A/B experiment?
This problem tests your ability to design a rigorous A/B experiment for a consumer-facing AI product, focusing on identifying interference, selecting appropriate metrics, and addressing statistical validity.
Analytics & ExperimentationOnsiteA/B TestingExperiment DesignMetrics - AnthropicHardSoftware EngineerHow do you lead under risk and uncertainty?
This question evaluates leadership competencies—risk assessment, stakeholder management, conflict resolution, and decision-making under uncertainty in engineering contexts.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerHow do you review a design document?
This question assesses a candidate's ability to critically evaluate technical design documentation by identifying architectural risks, scalability bottlenecks, and gaps in operational planning.
Software Engineering FundamentalsOnsiteSystem DesignCode ReviewReliability - AnthropicMediumSoftware EngineerHow to Handle the First-Round Interview at an AI Safety Lab
A structured prompt for the earliest conversation in the loop at a lab whose mission is AI safety, where most of the time goes to why you want to work there specifically and how you think about the risks of the technology, not resume review. Tests depth, specificity, and whether your safety views connect to real experience.
Behavioral & LeadershipOnsitebehavioralmotivationai-safety - AnthropicMediumSoftware EngineerHow 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 EngineerHow 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 EngineerIdentify 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 - AnthropicMediumSoftware EngineerIdentify the Most Important AI Safety Risk
Tests your ability to analyze AI alignment failure modes—specifically sycophancy and emotional over-reliance—and formulate rigorous evaluation metrics, training mitigations, and product-level guardrails.
Machine LearningHR ScreenAI SafetyRLHFSycophancy - AnthropicMediumSoftware EngineerImplement Parallel Image Processing
This question evaluates competency in concurrent and parallel processing, practical image manipulation with Python libraries (Pillow), resource management for memory and file I/O, robust error handling, and performance measurement.
Coding & AlgorithmsOnsite - AnthropicHardSoftware EngineerImplement Persistent Memoization LRU Cache
This problem tests your ability to design a decorator that memoizes function results using an LRU policy while ensuring the cache survives process restarts via disk serialization.
Coding & AlgorithmsOnsitePythonLRU CacheDecorator - AnthropicMediumSoftware EngineerImplement Python LRU cache with args and persistence
This question evaluates a candidate's ability to design and implement an LRU cache in Python that supports variable-length positional and keyword arguments with canonical, deterministic hashing for semantically equivalent calls and O(1) get/put via a hash map plus a doubly linked list; it falls under the Coding & Algorithms domain and primarily tests practical implementation skills, API robustness, hashing/equality subtleties, and algorithmic complexity guarantees. The persistence follow-up evaluates understanding of serialization and storage design — on-disk formats, versioning, and atomic write strategies — and compares trade-offs between binary pickle and JSON-based serialization in terms of security, compatibility, and performance, reflecting both conceptual design and practical system-level considerations.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerImplement Python LRU cache with varargs
This question evaluates a candidate's ability to implement an LRU caching mechanism in Python, including decorator design, argument canonicalization for positional args, *args, and **kwargs, handling unhashable inputs, eviction semantics, cache metadata operations (clear, cache_info), and JSON-based persistence and versioning.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerImplement Task Management and Duplicate Detection
This problem tests your ability to design an in-memory task management system with concurrency-aware state tracking and implement an efficient file-deduplication routine using hashing.
Coding & AlgorithmsTechnical ScreenData StructuresHashingConcurrency - AnthropicMediumSoftware EngineerImplement a Banking System
This question evaluates skills in designing and implementing a stateful in-memory banking system, covering account modeling, transfer lifecycle and expiration handling, balance management, and tracking aggregate outgoing amounts.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerImplement a Batch Image Processor
Design and implement an in-memory image transformation engine that applies sequential operations (grayscale, brightness scaling, nearest-neighbor resizing) over a batch of images efficiently.
Coding & AlgorithmsTechnical ScreenParallelismMultiprocessingImage Processing - AnthropicEasySoftware EngineerImplement a Duplicate-File Reporter
Implement an efficient file system scanner that identifies duplicate files while minimizing disk I/O and gracefully handling filesystem errors.
Software Engineering FundamentalsTechnical Screenfile-systemio-optimizationhashing - AnthropicMediumSoftware EngineerImplement a Least-Recently-Used Cache
This question evaluates a candidate's ability to design and implement an efficient in-memory cache with eviction behavior, testing understanding of data structure selection, state management, and time/space complexity under capacity constraints.
Coding & AlgorithmsOnsite - AnthropicHardSoftware EngineerImplement a Longest-Match Tokenizer
Design and implement a greedy longest-match text tokenizer that validates vocabulary, supports configurable unknown-token coalescing, and emits token IDs alongside their exact substring matches.
Coding & AlgorithmsOnsitetriestringnlp - AnthropicMediumSoftware EngineerImplement a Parallel Image Processor
Design and implement a concurrent batch image processor that executes a sequence of matrix transforms across worker threads or processes while isolating per-job failures.
Coding & AlgorithmsTechnical Screenconcurrencymultithreadingfault-tolerance - AnthropicHardSoftware EngineerImplement a Time-Aware Task Manager
Design an in-memory task manager supporting per-user task versioning, time-to-live (TTL) expiration, and point-in-time historical queries.
Coding & AlgorithmsTechnical ScreenBinary SearchData StructuresDesign - AnthropicHardSoftware EngineerImplement a hierarchical file store
This problem tests your ability to design a hierarchical file system data structure and implement operations for directory traversal, file manipulation, and path normalization.
Coding & AlgorithmsOnsiteTreeTrieData Structures - AnthropicMediumSoftware EngineerImplement an in-memory DB with TTL backup/restore
Implement an in-memory nested key-value store supporting field-level time-to-live (TTL) expiration and snapshot backup/restore operations.
Coding & AlgorithmsOnline Assessmentdata-structuresdesignhash-map - AnthropicHardSoftware EngineerImplement and analyze custom attention
This question evaluates implementation and analysis skills for scaled dot-product attention, testing competencies in efficient tensorized PyTorch coding, numerical stability and mixed-precision handling, masking semantics (causal and padding), multi-head shape correctness, and unit-test validation including gradient and edge-case behavior.
Machine LearningOnsite - AnthropicMediumSoftware EngineerImplement and derive backprop from scratch
This question evaluates understanding and practical implementation of neural network fundamentals, specifically analytic backpropagation and gradient derivation, numerically stable binary cross-entropy computation, parameter initialization, gradient descent updates, and gradient checking.
Machine LearningOnsite - AnthropicMediumSoftware EngineerImplement crawler, dedup, and persistent LRU
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Implement crawler, dedup, and persistent LRU states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite
Anthropic