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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
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- 11
- Topics
- 8
- Languages
Showing 421–450 of 3640 results
- AnthropicHardSoftware EngineerDesign 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 EngineerDesign 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 - AnthropicHardMachine Learning EngineerDesign an inference routing and scheduling layer
This question evaluates system-design and production machine learning engineering skills, specifically distributed systems, routing and scheduling, multi-tenant isolation, caching, dynamic batching, and capacity planning for heterogeneous GPU/CPU inference backends.
ML System DesignOnsite - AnthropicMediumSoftware EngineerDesign and implement a Python solution
This question evaluates Python programming proficiency, algorithm design, data structure selection and justification, modular coding practices, unit testing, and time/space complexity analysis.
Coding & AlgorithmsOnsite - AnthropicHardSoftware EngineerDesign 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 - AnthropicMediumSoftware EngineerDesign file deduplication at scale
This question evaluates understanding of file-system algorithms, hashing and deduplication techniques, scalable I/O and memory management, and correctness considerations for hash collisions, and it belongs to the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - AnthropicHardSoftware EngineerDesign 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 - AnthropicMediumSoftware EngineerDesign high-throughput hashing for kernels
This question evaluates understanding of cache-efficient, high-throughput hash lookup design and related competencies such as hashing strategies, probe behavior, memory layout, vectorization, bitwise optimizations, prefetching, alignment, and microarchitectural performance trade-offs.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerDetect duplicate files by content
This question evaluates filesystem traversal, efficient I/O and memory use, hashing strategies for content comparison, duplicate-detection algorithms, and time/space complexity analysis.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerDiscuss Ethical Judgment and Unwanted Work
Tests a candidate's self-awareness, ethical responsibility, and ability to navigate professional disagreements or undesirable tasks while maintaining team trust and high standards.
Behavioral & LeadershipOnsitebehavioralethicsleadership - AnthropicMediumSoftware EngineerDiscuss culture and mission alignment
This question evaluates alignment with organizational mission, ethical and safety judgment, decision-making under ambiguity, receptiveness to blunt feedback, collaboration style, and practices for sustaining engineering quality—core behavioral and leadership competencies for software engineers.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerDistribute 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 EngineerEstimate FFN Compute, Memory, and Sharding Communication
Estimate standard FFN FLOPs, parameter and activation bytes, and sharding communication, then compare compute, HBM, and network limits with explicit layout assumptions.
ML System DesignOnsite - AnthropicHardSoftware EngineerEstimate VRAM and compare model parallelism
This question tests the ability to calculate memory overhead for transformer model parameters and activation buffers, while evaluating the architectural trade-offs between tensor and pipeline parallelism for large-scale training.
ML System DesignOnsiteDistributed SystemsGPU ArchitectureTransformer Training - AnthropicMediumSoftware EngineerExplain Anthropic motivation and leadership stories
This question evaluates leadership, ethical reasoning, cultural fit, communication, and project ownership, targeting Behavioral & Leadership competencies for a software engineer role.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerExplain How You Resolved a Professional Conflict
Explain a professional conflict through fair opposing views, shared criteria, a concrete resolution process, personal adjustments, and follow-through.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerExplain Ownership of a Project Business Metric
Tests an engineer's ability to define, instrument, and own business or platform metrics, ensuring alignment with technical outcomes while actively managing guardrails and proxy risks.
Behavioral & LeadershipOnsiteBehavioralMetrics & TelemetryEngineering Leadership - AnthropicHardSoftware EngineerExplain Your AI Safety Values
Assesses how an engineer conceptualizes AI safety and risk, translates ethical principles into concrete engineering trade-offs, and navigates organizational friction or ambiguity when escalating potential harms.
Behavioral & LeadershipOnsiteAI SafetyBehavioralRisk Management - AnthropicMediumMachine Learning EngineerExplain batch inference design
This question tests your ability to design a robust, production-grade batch inference pipeline, focusing on data consistency, system reliability, and scalability.
Machine LearningOnsiteSystem DesignMLOpsBatch Processing - AnthropicMediumSoftware EngineerExplain career goals and cultural alignment
Explain career goals and cultural alignment 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 - AnthropicHardMachine Learning EngineerExplain management style, execution strategy, and culture choices
This question evaluates leadership, people-management, execution strategy, and product-oriented decision-making within a machine learning engineering context, covering conflict resolution, low-performer handling, fair calibration, strategy for ambiguous ML products, retrospectives, and culture-fit reasoning.
Behavioral & LeadershipOnsite - AnthropicMediumMachine Learning EngineerExplain multithreading vs multiprocessing
This question tests your conceptual understanding of how process-based and thread-based concurrency models leverage hardware resources and their respective trade-offs in the context of Python and high-performance ML workloads.
Software Engineering FundamentalsOnsiteConcurrencyPythonOperating Systems - AnthropicHardSoftware EngineerExplain projects and handle AI-safety conflicts
This question evaluates leadership, technical ownership, communication, trade-off analysis, ethical reasoning, and judgment on AI safety by asking candidates to describe projects and defend value-driven decisions.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerExplain the Most Complex Situation You Have Handled
Explain a complex professional situation through conflicting constraints, personal responsibility, evidence-based decisions, coordination, and lessons from the outcome.
Behavioral & LeadershipOnsite - AnthropicMediumMachine Learning EngineerFill In the Sampling and Decode Loop of an LLM Inference Notebook
Anthropic Fellows final-round practice: complete temperature/top-k/top-p sampling and a batched KV-cache decode loop in a Colab notebook so greedy output matches model.generate.
Machine LearningOnsiteAnthropic FellowsAI Safety Fellowshipllm-inference - AnthropicMediumSoftware EngineerFind Duplicate Files
This question evaluates a candidate's skills in file-system traversal, content deduplication strategies, hashing, large-file I/O handling, concurrency, and robustness to errors and file changes during scans.
Coding & AlgorithmsOnsite - AnthropicHardSoftware EngineerFind Duplicate Files by Content
This question evaluates the ability to parse file-system-style input, group files by identical content, and manage deduplication using appropriate data structures and algorithms.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerFind Duplicate Files by Content in a Directory Tree and Explain CPU vs I/O Costs
Walk a directory tree and report every group of files with identical contents, printing nothing when there are no duplicates. It tests staged filtering by size and hashes, streaming reads of large files, link and error handling, and reasoning about whether the job is CPU-bound or I/O-bound.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerFind 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 - AnthropicMediumSoftware EngineerFind and remove duplicate files
This question evaluates the ability to design scalable file deduplication algorithms, specifically testing knowledge of hashing strategies, collision handling, memory and I/O optimization, handling very large files, incremental/resumable operation, and complexity and trade-off analysis.
Coding & AlgorithmsOnsite
Anthropic