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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
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- 546
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- 11
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Showing 7651–7680 of 9403 results
- Scale AIEasySoftware EngineerDesign a Streaming Job Scheduler
This question evaluates task scheduling, deadline-based prioritization, dependency management, and distributed coordination competencies, encompassing algorithmic/data-structure reasoning as well as correctness under concurrency and failure conditions.
System DesignTechnical Screen - Scale AIMediumSoftware EngineerDesign a large-scale ticketing system
This question evaluates skills in large-scale system design, including distributed systems, concurrency control, transactional correctness, data modeling, API design, and integration with external payment providers.
System DesignTechnical Screen - Scale AIEasySoftware EngineerDesign an LLM API pipeline
This question evaluates competency in integrating hosted LLMs into user-facing applications, including API request design, prompt engineering for structured output, output validation, latency and failure handling, and production readiness.
ML System DesignOnsite - Scale AIMediumSoftware EngineerDesign and Simulate a Four-Player Card Game
Work through a three-stage object-oriented card game covering dealing, follow-suit trick state, configurable scoring, and deterministic tests.
Software Engineering FundamentalsTechnical Screen - Scale AIMediumSoftware EngineerDesign pipeline using classification and embedding services
This question evaluates a candidate's proficiency in ML system design, covering API design, service orchestration, data storage modeling, scalability strategies, and reliability/observability when integrating black-box classification and embedding services.
ML System DesignOnsite - Scale AIEasyMachine Learning EngineerExplain LLM post-training methods and tradeoffs
This question assesses the candidate's understanding of the LLM post-training pipeline, specifically how to transition a foundation model into a helpful, safe assistant through various alignment techniques.
Machine LearningOnsiteLLMAlignmentRLHF - Scale AIHardMachine Learning EngineerExplain Transformers, attention, decoding, RL, and evaluation
This question evaluates understanding of transformer architectures, self- and cross-attention mechanisms, autoregressive decoding and sampling strategies, reinforcement learning–based fine-tuning (RLHF), evaluation methodologies, and training/inference optimization techniques.
Machine LearningTechnical Screen - Scale AIMediumSoftware EngineerFind LCA in a N-ary tree via DFS
This question evaluates understanding of tree algorithms and recursive DFS traversal for computing the lowest common ancestor in an N-ary tree, including handling node references, subtree detection, and correctness in a single traversal.
Coding & AlgorithmsTechnical Screen - Scale AIEasyMachine Learning EngineerHandle customer engagement and manager-rating questions
This question evaluates stakeholder management, leadership principles, conflict-resolution skills, and self-awareness, emphasizing interpersonal communication, influence, and accountability.
Behavioral & LeadershipOnsite - Scale AIHardSoftware EngineerImplement Dependency-Aware Task Scheduler
Design and implement a dependency-aware task scheduler that supports dynamic task registration, cycle detection, priority-based ready task retrieval, and state transitions.
Coding & AlgorithmsTechnical ScreenGraphHeapDesign - Scale AIMediumSoftware EngineerImplement Hook and Modify UI Interactions
This question evaluates a candidate's ability to implement reusable React hooks, manage asynchronous data fetching with loading/error/refetch semantics, transform API responses, and wire component state for modal, collapsible list, and button-driven UI interactions.
Software Engineering FundamentalsTechnical Screen - Scale AIEasySoftware EngineerImplement a Dependency-Aware Task Scheduler
This question evaluates skills in dependency management, deadline-driven scheduling and algorithmic data-structure design, focusing on handling directed acyclic graphs and ordering constraints.
Coding & AlgorithmsTechnical Screen - Scale AIMediumSoftware EngineerImplement a Task Processor
This problem tests your ability to manage tasks with dependencies using a combination of graph-based topological sorting (Kahn's algorithm) and a priority queue to ensure deadlines are respected.
Coding & AlgorithmsTechnical ScreenGraphsHeapsTopological Sort - Scale AIEasyMachine Learning EngineerImplement multi-head attention and LLM sampling
This problem tests your ability to implement the core mechanics of a Transformer's attention mechanism and the logic required to sample the next token from a model's output logits.
Coding & AlgorithmsOnsiteTransformersDeep LearningNumPy - Scale AIMediumMachine Learning EngineerImplement universal adversarial attack on GPT-2
Machine learning robustness prompt on safely evaluating universal adversarial prompts for GPT-2, covering threat modeling, differentiable optimization concepts, transferability, metrics, safety controls, and mitigation strategies without deployment-ready jailbreak details.
Machine LearningTechnical Screen - Scale AIEasySoftware EngineerPresent a Metrics-Driven Technical Project
Tests your ability to present a past technical initiative clearly to peers, articulating technical architecture, quantifiable metrics, personal ownership, and real-world tradeoffs.
Behavioral & LeadershipOnsitebehavioralsystem architectureproject deep-dive - Scale AIMediumSoftware EngineerQuantify impact of your projects using STAR
This question evaluates a candidate's ability to use the STAR method to articulate project ownership, quantify technical and business impact, and demonstrate leadership, communication, and metrics literacy for a Software Engineer role.
Behavioral & LeadershipTechnical Screen - Scale AIMediumSoftware EngineerSchedule Ready Tasks by Deadline
This question evaluates understanding of task scheduling and dependency management in directed acyclic graphs, along with algorithmic selection and data-structure-based optimization for repeated minimum-deadline retrieval.
Coding & AlgorithmsTechnical Screen - Schneider ElectricMediumSoftware EngineerCompare JavaScript == and === operators
This question evaluates understanding of JavaScript equality semantics and type coercion, assessing a candidate's competency in language-specific comparison behavior and recognition of subtle runtime differences.
Software Engineering FundamentalsTechnical Screen - Schneider ElectricMediumSoftware EngineerDescribe debugging approach for software issues
This question evaluates debugging and troubleshooting skills, observability and tooling proficiency, prioritization, and cross-team communication within the Behavioral & Leadership domain of software engineering.
Behavioral & LeadershipTechnical Screen - Schneider ElectricMediumSoftware EngineerReflect on learnings from prior co-op experience
This question evaluates communication, team collaboration, technical problem-solving, stakeholder empathy, and reflective leadership competencies developed during a co-op or internship.
Behavioral & LeadershipTechnical Screen - SchonfeldMediumData ScientistCompute probability last passenger gets own seat
This question evaluates a candidate's understanding of probability theory, combinatorics, and reasoning about sequential random processes, with emphasis on symmetry and conditional dependence.
Coding & AlgorithmsOnline Assessment - SchonfeldMediumData ScientistFind smallest N for 5-and-21 sums
This question evaluates understanding of integer linear combinations and elementary number theory, framed as a Frobenius coin problem that examines representability using non-negative multiples of 5 and 21.
Coding & AlgorithmsOnline Assessment - SchwabEasyJava DeveloperExplain Spring Dependency Injection and Choose an Injection Style
Tests core knowledge of Spring's Inversion of Control (IoC) container, trade-offs between constructor, setter, and field injection, bean lifecycle, and dependency resolution strategies.
Software Engineering FundamentalsOnsiteJavaSpringDependency Injection - SchwabEasyJava DeveloperReview a Spring REST Controller for Correctness and Per-Request Waste
Analyze a flawed Spring Boot REST controller to identify anti-patterns, HTTP status code misuses, concurrency hazards, and unnecessary per-request object allocations. Refactor the implementation to follow production-grade enterprise standards.
Software Engineering FundamentalsOnsiteJavaSpring BootREST API - ScribdMediumSoftware EngineerBehavioral: Reason for Leaving, Proudest Project, Handling Ambiguity, and a Trade-off
This set of behavioral prompts evaluates a candidate's self-awareness, project ownership, adaptability under uncertainty, and technical pragmatism.
Behavioral & LeadershipOnsiteBehavioralLeadershipCommunication - ScribdMediumSoftware EngineerMany-to-Many Schema Design With a Join Table, Composite Primary Key, and Queries
Design a relational schema modeling a many-to-many relationship between documents and tags using a join table with a composite primary key, index both lookup directions, and write queries handling outer joins and relational division.
Data Manipulation (SQL/Python)OnsiteSQLDatabase DesignPostgreSQL - ScribdMediumSoftware EngineerMost Popular Actors Query When Object IDs Mix Movies and People With Multiple Roles
A data query question about ranking the most popular actors when an object ID can refer to either a movie or a person, and one person can hold several roles in the same movie. It tests clarifying the popularity metric, filtering to actor credits, deduplicating person and movie pairs, checking object types, and defining a tie policy.
Data Manipulation (SQL/Python)Onsite - ScribdMediumSoftware EngineerProduct Event Tracking and Analytics Pipeline With Flexible Schema and Retention
This question tests the architectural design of a scalable event-tracking pipeline capable of handling heterogeneous JSON schemas, choosing appropriate storage tiers for analytical queries, and managing data lifecycle policies.
System DesignOnsiteData PipelineSchema DesignStorage - ScribdMediumSoftware EngineerProduction-Ready Event Ingestion Handler: Validation, Idempotent Writes, DLQ, Metrics
Tests your ability to write production-grade ingestion code that enforces strict schema validation, guarantees idempotent persistence, handles retries and Dead-Letter Queue (DLQ) routing, and emits operational metrics.
Software Engineering FundamentalsOnsitedata-pipelinesvalidationsystem-reliability
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