practice a little every day, paws crossed ♡
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 1171–1200 of 9403 results
- AnthropicMediumSoftware EngineerReview and Scale an Inference Service Design
Tests the ability to architect a high-throughput ML inference service under strict latency SLAs, including dynamic batching, hardware capacity estimation, admission control, and multi-model routing.
ML System DesignTechnical Screenml-system-designdistributed-systemsgpu-inference - AnthropicHardSoftware EngineerRoute and Batch Inference with Eight GPUs
Design an inference routing, dynamic batching, and scheduling system across a fixed pool of eight 80GB GPUs serving both large and small language models under strict latency and memory constraints.
ML System DesignTechnical Screenml-systemsllm-inferencegpu-scheduling - AnthropicMediumSoftware EngineerSame-Domain Web Crawl (BFS)
Implement a breadth-first search crawler that traverses pages starting from a seed URL, filtering for pages sharing the same domain and properly deduplicating visited URLs.
Coding & AlgorithmsOnsitebfsgraphstring-parsing - AnthropicMediumSoftware EngineerSame-Host Web Crawler: Single-Threaded, Then Concurrent with a Thread-Safe Visited Set
Build a web crawler that starts from one URL, follows links only on the same hostname, strips URL fragments and fetches each page once, first single-threaded and then concurrently. It tests graph traversal, URL normalization, a thread-safe visited set and correct termination of concurrent work.
Software Engineering FundamentalsOnsite - AnthropicMediumSoftware EngineerScale a Thumbnail-and-Watermark Pipeline With Worker Processes
Design a batch pipeline that produces a resized thumbnail with a corner watermark for every uploaded photo, then extend it to run across a bounded pool of worker processes. Tests resource lifecycle, atomic output writes, per-item failure isolation, and what to pass between processes.
Software Engineering FundamentalsOnsitemultiprocessingsystem-designpython - AnthropicHardSoftware EngineerScale 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 - AnthropicHardMachine Learning EngineerSchedule Large and Small Model Inference on an Eight-GPU Pool
Design an inference scheduler for a shared 8-GPU node that co-locates single-GPU small models and all-reduce 8-GPU large models. The design must address gang scheduling, prefix cache reuse, deadline-aware priorities, and overload mitigation.
ML System DesignTechnical Screenml-system-designgpu-schedulingdistributed-inference - AnthropicHardSoftware EngineerSchedule 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 - AnthropicHardSoftware EngineerSimulate Threshold Infection Efficiently
Simulate a synchronous threshold-based infection process on a grid using an incremental multi-source BFS to achieve optimal linear time complexity.
Coding & AlgorithmsOnsiteBFSGraphMatrix - AnthropicMediumSoftware EngineerSimulate stack traces from logs
This question evaluates stack-based simulation for computing exclusive execution time in nested function call logs and stream-processing concepts for handling equal timestamps, slight reordering, and detection of N consecutive categorical events.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerSolve programming task with follow-ups
This question evaluates algorithmic problem-solving skills, including core algorithm implementation, handling a consecutive-N-element constraint, and designing an optimization that leverages suffix-related information.
Coding & AlgorithmsTechnical Screen - AnthropicMediumSoftware EngineerSystem 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 - AnthropicMediumData ScientistTell Me About a Metric You Built That Changed a Real Decision
A behavioral prompt asking the candidate to walk through a time they invented or redefined a metric, prove it was measuring the right thing, and show it actually changed what the business did next.
Behavioral & LeadershipHR Screenbehavioralmetricscommunication - AnthropicMediumSoftware EngineerTime-Based Key-Value Store
Design a versioned key-value store that supports storing values at specific timestamps and retrieving the most recent value at or before a given timestamp.
Coding & AlgorithmsOnsitebinary-searchhash-tabledesign - AnthropicMediumMachine Learning EngineerWalk Through Your Work Background and Explain Your Concerns About AI Safety
A recruiter screen question for a machine learning engineering role at an AI research company: give a concise overview of your work background, then explain the concerns you have about AI safety. It tests whether you can tell a focused career story and discuss safety risks with specific mechanisms, calibrated views and a link to the role.
Behavioral & LeadershipHR Screen - AnthropicHardSoftware EngineerWalk through a recent technical project
This question evaluates a candidate's engineering depth and leadership competency by requiring a structured walkthrough of a recent technical project covering problem framing, architectural trade-offs, data modeling and APIs, scalability and reliability, testing and rollout, and measurement of outcomes.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerWhy Anthropic and its values?
This question evaluates a candidate's culture fit, value alignment, integrity under pressure, and critical thinking within the Behavioral & Leadership category for a software engineering role.
Behavioral & LeadershipTechnical Screen - AnthropicMediumSoftware EngineerWhy Anthropic, What AI Safety Means to You, and AI Misuse: Recruiter Screen Prep
Prepare for a recruiter screen at an AI safety lab that spends most of its time on motivation and safety views: why you are leaving, why this lab over others, what AI safety means to you, misuse scenarios, the biggest risks and benefits of advanced AI, and an underrated problem. It tests depth, honesty and preparation.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerWhy Join an AI Safety-Focused Lab, and What Is Your View on AI Safety?
A recruiter-call question for a senior software engineer at an AI lab: explain why you want to join this particular company and share your own view on AI safety. It tests whether your motivation is specific and sincere, whether you can state a reasoned, calibrated position on AI risk, and how you connect safety to engineering work.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerWhy Work on AI Safety
Assesses your motivation and understanding of AI safety, focusing on how engineering skills intersect with frontier risks, mitigation strategies, and intellectual honesty.
Behavioral & LeadershipHR ScreenAI SafetyBehavioralCulture Fit - AnthropicMediumSoftware EngineerWord Search in a Letter Grid
This problem tests the ability to implement a backtracking search on a 2D grid, optimized with a Trie data structure to efficiently search for multiple strings simultaneously.
Coding & AlgorithmsOnsiteTrieBacktrackingDFS - AntraMediumSoftware EngineerCharacter Frequency Count in a String
This problem tests your ability to manipulate strings and utilize hash maps to count character frequencies while maintaining the original order of character appearance.
Coding & AlgorithmsTechnical ScreenStringsHash MapAlgorithms - AntraEasySoftware EngineerExplain core Java and Spring fundamentals
This question evaluates core competencies in Java and Spring, covering data structures and collections, object-oriented design (SOLID), hash-based collections and concurrency primitives, immutability and string handling, exception handling, Spring IoC/DI and AOP, bean lifecycle and annotations, and functional collection processing via the Stream API. Commonly asked in Software Engineering Fundamentals interviews for backend Java/Spring roles, it checks both conceptual understanding and practical application by assessing architectural reasoning, concurrency and thread-safety knowledge, and familiarity with framework conventions and APIs.
Software Engineering FundamentalsTechnical Screen - AntraMediumSoftware EngineerJava and Object-Oriented Design Fundamentals
This problem tests your understanding of interface design, the Liskov Substitution Principle, and proper usage of Java Collections in a Spring-managed context.
Software Engineering FundamentalsTechnical ScreenJavaSpringSOLID - AntraMediumSoftware EngineerLongest Substring Without Repeating Characters
This problem tests your ability to implement an efficient sliding window technique using a hash map to track character indices and maintain a valid substring constraint.
Coding & AlgorithmsTechnical ScreenSliding WindowHash MapString - AnyscaleMediumSoftware EngineerDesign 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 - AppleHardSoftware EngineerASIC Verification Fundamentals Across SystemVerilog UVM CDC and Architecture
Review a broad ASIC verification set covering SystemVerilog semantics, UVM lifecycle and communication, random constraints, clock-domain crossing, FIFO sizing, timing, clock division, cache coherence, and pipeline hazards. Strong responses distinguish simulation from hardware, define assumptions, derive quantities, compare trade-offs, and use precise examples.
Software Engineering FundamentalsOnsite - AppleMediumMachine Learning EngineerAnalyze vision model failures
This question evaluates proficiency in computer vision machine learning fundamentals (including bias–variance tradeoffs, overfitting, class imbalance, evaluation metrics, threshold selection, calibration, and data leakage), probabilistic reasoning for performance interpretation, and production model diagnosis and root-cause analysis.
Machine LearningOnsite - AppleMediumSoftware EngineerAnswer OoO, caches, and memory-system questions
This question evaluates core computer-architecture and system-level skills—covering out-of-order execution structures, branch prediction (gshare) mechanics, register renaming/RAT tracing, VLIW versus superscalar tradeoffs, cache coherence protocols, load/store subsystem behavior, copy-on-write after fork, cache indexing math, VIPT aliasing, and asynchronous FIFO design—and is categorized under Software Engineering Fundamentals. It is commonly asked because it probes a candidate’s microarchitectural and OS understanding, performance reasoning, and ability to explain low-level (microarchitecture and system-level) concepts and interactions without requiring full ISA-specific implementations.
Software Engineering FundamentalsTechnical Screen - AppleMediumSoftware EngineerBehavioral Round: Judgment, Prioritization, and Influence
This set of prompts assesses your ability to navigate complex workplace dynamics by evaluating your decision-making frameworks, adaptability under pressure, and interpersonal influence strategies.
Behavioral & LeadershipOnsiteCommunicationLeadershipConflict Resolution
Anthropic
Apple