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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
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Showing 9361–9390 of 9403 results
- xAIMediumSoftware EngineerDesign a Durable Key-Value Cache with File-System Persistence
This question evaluates a candidate's ability to design durable in-memory data structures and persistence strategies, including reasoning about crash recovery, durability guarantees, and performance trade-offs.
System DesignTechnical Screen - xAIMediumSoftware EngineerDesign a Least Frequently Used (LFU) Cache with O(1) Operations
This question evaluates understanding of data structures and algorithm design for implementing a Least Frequently Used (LFU) cache with O(1) get and put operations, emphasizing frequency tracking and least-recently-used tie-breaking.
Coding & AlgorithmsOnsite - xAIMediumSoftware EngineerDesign a Rate Limiter with Per-User Token Quotas
This question evaluates a candidate's ability to design distributed, low-latency rate limiting with heterogeneous per-user quotas, covering competencies in state modeling, consistency, caching, and scalable architecture.
System DesignOnsite - xAIMediumFrontend EngineerDesign a Real-Time Collaborative Document Editor with Concurrent Edits
A system design question for a frontend engineer: design a collaborative document editor where several people edit the same document at once and see each other's changes in near real time. It tests conflict resolution for concurrent edits, client-side state, the sync protocol, persistence and presence.
System DesignOnsite - xAIMediumSoftware EngineerDesign a Recoverable Iterator
Design a forward-only iterator wrapper that supports saving and restoring cursor state via checkpoints, testing buffering strategies and memory management.
Coding & AlgorithmsTechnical Screendesigndata-structuresiterators - xAIMediumSoftware EngineerDesign a Retrieval-Augmented Generation (RAG) System
This question evaluates understanding and engineering competency for retrieval-augmented generation (RAG) systems, covering offline indexing and online query planes, retrieval quality, prompt assembly, grounded generation with citations, and production monitoring; the domain is ML System Design.
ML System DesignOnsite - xAIMediumSoftware EngineerDesign a URL Shortening Service: Code Generation, Redirect Path, and Scaling
A system design question asked as a 30-minute screen with no coding: design a URL shortening service that turns long URLs into short links and redirects visitors. It tests requirement scoping, capacity estimates, collision-free code generation, a fast read path, storage, scaling and failure handling.
System DesignOnsite - xAIMediumSoftware EngineerDesign a backend for an online checkers game
This problem tests your ability to design a state-aware, real-time multiplayer system that ensures data consistency, enforces complex game rules, and manages turn-based concurrency.
System DesignOnsiteWebSocketsConcurrencyAPI Design - xAIHardMachine Learning EngineerDesign a house-price prediction workflow
Design a house-price prediction workflow evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningTechnical Screen - xAIEasySoftware EngineerDesign a multi-level API rate limiter
This question assesses the ability to design a scalable, multi-tenant rate limiting service that supports hierarchical policies and global traffic coordination.
System DesignTechnical ScreenDistributed SystemsScalabilityCaching - xAIHardSoftware EngineerDesign and Implement a URL Shortening Service
Tests your ability to design a globally distributed, highly available URL shortening service capable of handling high read/write throughput with sub-millisecond redirection latency and collision-free ID generation.
System DesignOnsitesystem-designdistributed-systemscaching - xAIMediumMachine Learning EngineerDynamic Batching Decode Loop for a Mock Language Model with Slot Refilling
An LLM inference coding question: write the generation loop for a mock language model that returns one next token per sequence in a batch. Requests finish at different steps on a stop token or a max-token limit, and freed batch slots must be refilled from a waiting queue, testing state tracking and batching logic.
Software Engineering FundamentalsOnsite - xAIMediumMachine Learning EngineerExplain Data Collection Choices and Their Impact on Downstream Model Performance
A machine learning screening question: explain how the data for a project on your resume was collected and processed, then discuss how data choices affect performance on downstream tasks. It tests first-hand knowledge of data pipelines, causal reasoning about data quality, and how to measure data effects.
Machine LearningOnsite - xAIMediumSoftware EngineerExplain and Implement Strings
This question evaluates understanding of string data structures, memory layout, ownership and move semantics in Rust, and algorithmic complexity related to copying and performance.
Coding & AlgorithmsTechnical Screen - xAIMediumSoftware EngineerExplain arrays and memory layout
This question evaluates understanding of arrays, their contiguous memory representation including element size, alignment and indexing arithmetic, along with time-complexity analysis for access, insertion and deletion and implications for cache locality.
Coding & AlgorithmsTechnical Screen - xAIMediumSoftware EngineerExplain process vs thread and memory-sharing risks
This question tests the conceptual understanding of process versus thread architecture and the synchronization challenges inherent in shared-memory multithreading.
Software Engineering FundamentalsTechnical ScreenOperating SystemsConcurrencyMultithreading - xAIMediumSoftware EngineerExplain strings, moves, and concurrency
This question evaluates understanding of string data structures, ownership and move semantics (including Rust-specific move behavior), and concurrency models such as threads versus asynchronous coroutines, testing competencies in memory management, performance analysis, and concurrent programming.
Coding & AlgorithmsTechnical Screen - xAIMediumMachine Learning EngineerFind All Faulty GPU Nodes with Parallel Group Tests That Cannot Share Nodes
An algorithm design question about finding every faulty GPU node when the only tool is a group test that fails if any node in the set is bad. Tests need at least two nodes and parallel tests cannot share nodes, so it tests adaptive testing strategies, identifiability, and cost in rounds and tests.
Software Engineering FundamentalsOnsite - xAIHardSoftware EngineerFind kth element and sliding-window kth in stream
This problem tests your ability to maintain order statistics in a streaming context, moving from a static selection problem to an efficient sliding-window implementation.
Coding & AlgorithmsTechnical ScreenQuickSelectHeapSliding Window - xAIMediumSoftware EngineerFlatten and unflatten nested Python structures
This problem tests recursion, type introspection, and data structure manipulation by requiring the implementation of flattening and reconstruction logic for arbitrarily nested lists and dictionaries.
Coding & AlgorithmsTechnical ScreenRecursionData StructuresSerialization - xAIHardMachine Learning EngineerGreedy Longest-Match Tokenizer for an LLM Data Pipeline
This question evaluates understanding of string-processing and greedy maximal-munch tokenization, as well as competency in designing efficient prefix-matching data structures and handling large-scale text preprocessing for LLM pipelines.
Coding & AlgorithmsOnsite - xAIMediumSoftware EngineerHow Would You Prevent Hallucinations in an LLM-Based System?
This question evaluates a candidate's understanding of hallucination in large language models, including underlying causes, detection, and system-level mitigation approaches, as well as their ability to reason about model reliability and failure modes.
Machine LearningHR Screen - xAIHardMachine Learning EngineerImplement Distributed Matrix Multiplication
This problem tests your ability to design a distributed matrix multiplication algorithm by partitioning large matrices across multiple worker nodes to minimize communication overhead.
Coding & AlgorithmsTechnical ScreenDistributed SystemsLinear AlgebraParallel Computing - xAIMediumSoftware EngineerImplement a Radix Cache for Integer Sequences
This question evaluates understanding of radix trees (prefix-compressed tries), sequence-oriented trie manipulation, and the maintenance of invariants like distinct branching and maximal compression, and belongs to the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - xAIMediumSoftware EngineerImplement a parallelized sort
This problem tests your ability to implement a parallelized version of Merge Sort using threads or a thread pool, focusing on partitioning, synchronization, and managing recursion depth.
Coding & AlgorithmsOnsiteAlgorithmsConcurrencyMerge Sort - xAIHardMachine Learning EngineerImplement a trie-based tokenizer
This question evaluates a candidate's competency in designing and implementing a production-grade subword tokenizer, covering trie-based longest-prefix matching, Unicode-aware text processing, normalization and casing impacts, whitespace/punctuation rules, fallback strategies, performance and memory trade-offs, versioning, and testing for edge cases. It is commonly asked in ML System Design interviews to assess practical implementation skills and conceptual trade-off reasoning for deterministic, scalable LLM preprocessing, and tests both practical application and conceptual understanding within the ML System Design domain.
ML System DesignTechnical Screen - xAIMediumFrontend EngineerImplement an Asynchronous React Typeahead
Implement a debounced React typeahead with stale-response protection, cancellation, loading/error states, keyboard selection, and accessible combobox semantics.
Software Engineering FundamentalsOnsite - xAIMediumMachine Learning EngineerImplement dynamic batching for token decoding
This question evaluates dynamic batching, per-request state management, and sequence-decoding correctness for language-model inference, including handling stop conditions, max-token limits, and maintaining a correct slot-to-request mapping.
Coding & AlgorithmsOnsite - xAIMediumData EngineerImplement two string utility functions
This question evaluates proficiency in string manipulation and text processing, including character counting, tokenization by spaces, case-sensitive comparisons, and preserving original word order.
Coding & AlgorithmsTechnical Screen - xAIEasySoftware EngineerIn-Memory Key-Value Database with Nested Transactions
This question evaluates understanding of in-memory data structures, transactional semantics (including nested transactions), and algorithmic complexity for implementing a key-value store that supports efficient GET/SET and rollback/commit operations.
Coding & AlgorithmsOnsite
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