xAI interview questions

Showing 1–30 of 53 results

• Answer technical-challenge and motivation questionsHard

  This question evaluates technical problem-solving depth, communication of impact, leadership and ownership, and intrinsic motivation and cultural fit by probing a candidate's most challenging engineering work and reasons for joining the team.

  xAISoftware EngineerBehavioral & LeadershipOnline Assessment
• Build a One-Pass Data Cleaning PipelineMedium

  This problem tests your ability to design a memory-efficient, scalable data streaming pipeline that processes raw web-scraped documents into a high-quality dataset for model pretraining.

  xAIData EngineerSystem DesignTechnical Screen
• Build a React Typeahead with Async Suggestions and Keyboard NavigationMedium

  A frontend coding question: build a React typeahead, a search input whose dropdown shows suggestions fetched asynchronously as the user types. The dropdown must support arrow keys, Enter, Escape and mouse selection, so it tests hooks, handling of out-of-order responses, accessibility and UI state.

  xAIFrontend EngineerSoftware Engineering FundamentalsOnsite
• Compute dasher pay from order eventsMedium

  This question evaluates a candidate's ability to process time-based event streams, manage overlapping active intervals, and compute aggregate payouts under concurrency constraints.

  xAISoftware EngineerCoding & AlgorithmsTechnical Screen
• Compute total active time per Twitter SpaceMedium

  This problem tests your ability to process chronological event streams to calculate overlapping or continuous active intervals and aggregate durations per category.

  xAISoftware EngineerCoding & AlgorithmsOnsite
• Constant-Time Insert, Remove, and Uniform Random SamplingHard

  This question evaluates the ability to design a data structure that supports constant-time insertions, removals, and uniform random sampling, testing concepts such as hashing, indexed storage, and randomized selection within the coding and algorithms domain.

  xAIMachine Learning EngineerCoding & AlgorithmsOnsite
• Contrast processes and threadsMedium

  This question evaluates understanding of operating system and concurrency fundamentals—specifically differences between processes and threads including memory isolation, resource ownership, scheduling, context-switch costs, inter-process communication versus in-process synchronization, failure isolation, and security.

  xAISoftware EngineerCoding & AlgorithmsTechnical Screen
• Describe your research and contributionsMedium

  Describe your research and contributions 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.

  xAIMachine Learning EngineerBehavioral & LeadershipTechnical Screen
• Design O(1) random-sampling setMedium

  This question evaluates a candidate's competency in data-structure design, randomized algorithms, and algorithmic complexity analysis within the Coding & Algorithms domain, with a focus on achieving expected O(1) operations for insert, remove, and uniform sampling.

  xAIMachine Learning EngineerCoding & AlgorithmsTechnical Screen
• Design a Collaborative Document EditorMedium

  Design collaborative editing with an explicit operation model, OT or CRDT convergence, durable history, reconnect recovery, access control, and separate presence state.

  xAIFrontend EngineerSystem DesignOnsite
• Design a Durable Key-Value Cache with File-System PersistenceMedium

  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.

  xAISoftware EngineerSystem DesignTechnical Screen
• Design a Least Frequently Used (LFU) Cache with O(1) OperationsMedium

  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.

  xAISoftware EngineerCoding & AlgorithmsOnsite
• Design a Rate Limiter with Per-User Token QuotasMedium

  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.

  xAISoftware EngineerSystem DesignOnsite
• Design a Real-Time Collaborative Document Editor with Concurrent EditsMedium

  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.

  xAIFrontend EngineerSystem DesignOnsite
• Design a Recoverable IteratorMedium

  Design a forward-only iterator wrapper that supports saving and restoring cursor state via checkpoints, testing buffering strategies and memory management.

  xAISoftware EngineerCoding & AlgorithmsTechnical Screen
• Design a Retrieval-Augmented Generation (RAG) SystemMedium

  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.

  xAISoftware EngineerML System DesignOnsite
• Design a URL Shortening Service: Code Generation, Redirect Path, and ScalingMedium

  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.

  xAISoftware EngineerSystem DesignOnsite
• Design a backend for an online checkers gameMedium

  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.

  xAISoftware EngineerSystem DesignOnsite
• Design a house-price prediction workflowHard

  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.

  xAIMachine Learning EngineerMachine LearningTechnical Screen
• Design a multi-level API rate limiterEasy

  This question assesses the ability to design a scalable, multi-tenant rate limiting service that supports hierarchical policies and global traffic coordination.

  xAISoftware EngineerSystem DesignTechnical Screen
• Design and Implement a URL Shortening ServiceHard

  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.

  xAISoftware EngineerSystem DesignOnsite
• Dynamic Batching Decode Loop for a Mock Language Model with Slot RefillingMedium

  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.

  xAIMachine Learning EngineerSoftware Engineering FundamentalsOnsite
• Explain Data Collection Choices and Their Impact on Downstream Model PerformanceMedium

  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.

  xAIMachine Learning EngineerMachine LearningOnsite
• Explain and Implement StringsMedium

  This question evaluates understanding of string data structures, memory layout, ownership and move semantics in Rust, and algorithmic complexity related to copying and performance.

  xAISoftware EngineerCoding & AlgorithmsTechnical Screen
• Explain arrays and memory layoutMedium

  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.

  xAISoftware EngineerCoding & AlgorithmsTechnical Screen
• Explain process vs thread and memory-sharing risksMedium

  This question tests the conceptual understanding of process versus thread architecture and the synchronization challenges inherent in shared-memory multithreading.

  xAISoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Explain strings, moves, and concurrencyMedium

  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.

  xAISoftware EngineerCoding & AlgorithmsTechnical Screen
• Find All Faulty GPU Nodes with Parallel Group Tests That Cannot Share NodesMedium

  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.

  xAIMachine Learning EngineerSoftware Engineering FundamentalsOnsite
• Find kth element and sliding-window kth in streamHard

  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.

  xAISoftware EngineerCoding & AlgorithmsTechnical Screen
• Flatten and unflatten nested Python structuresMedium

  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.

  xAISoftware EngineerCoding & AlgorithmsTechnical Screen