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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 1531–1560 of 9403 results
- AttentiveMediumSoftware EngineerDesign a Snapshot-Driven Product Catalog
Design a multi-tenant product catalog ingestion and serving system that processes periodic, complete merchant snapshots while deterministically layering administrator overrides, supporting atomic cutovers, and maintaining read consistency.
System DesignOnsitesystem-designe-commercedata-pipelines - AttentiveMediumSoftware EngineerEvaluate a Lisp-Style Prefix Expression Language With ADD, MULT and LET Variables
Implement an evaluator for a small Lisp-style prefix language with ADD and MULT, then extend it with LET variable bindings. It tests recursive parsing of nested expressions, settling ambiguous language rules before coding, and choosing a data structure for nested variable scopes.
Software Engineering FundamentalsOnsite - AttentiveMediumSoftware EngineerEvaluate a Scoped Lisp Expression
Implement a recursive descent or token-based interpreter to evaluate a scoped, Lisp-like arithmetic expression supporting addition, multiplication, and sequential variable bindings with shadowing.
Coding & AlgorithmsOnsiterecursionparsinghash-table - AttentiveHardData ScientistExplain switch to product analytics and company fit
This question evaluates a data scientist's product analytics and leadership competencies, including end-to-end decision ownership, prioritization of product metrics, communicating trade-offs between statistical rigor and speed, and influencing stakeholders within a B2B mobile messaging context that has compliance and deliverability constraints.
Behavioral & LeadershipTechnical Screen - AttentiveMediumSoftware EngineerFind Inclusive Index Ranges for Time-Window Queries on Timestamp-Sorted Logs
Given log timestamps sorted in non-decreasing order with possible duplicates, answer many inclusive time-window queries by returning the first and last index of the entries inside each window, where a window may extend past the data's time range. It tests O(log n) per-query boundary searches on sorted data with duplicate keys.
Coding & AlgorithmsTechnical Screen - AttentiveMediumSoftware EngineerRemove Adjacent Duplicate Runs of Length K
Implement a linear-time string reduction algorithm that repeatedly eliminates adjacent runs of k identical characters using a stack.
Coding & AlgorithmsTechnical Screenstackstringalgorithms - AttentiveMediumSoftware EngineerReturn Log Entries Within an Inclusive Time Range From a Sorted Log
Given an in-memory log sorted by integer timestamp, return every entry whose timestamp lies within an inclusive start and end time. The problem tests exact boundary handling with duplicate timestamps, empty results when the range misses the log, and locating a range efficiently in sorted data.
Coding & AlgorithmsOnsite - Auction.ComMediumData ScientistPresent a Clear Data Science Career Narrative
This question tests your ability to synthesize your past data science experiences into a cohesive, goal-oriented narrative that aligns with the specific requirements of a data-driven organization.
Behavioral & LeadershipTechnical ScreenBehavioralCommunicationStorytelling - AugerMediumSoftware EngineerShow the Technical Difficulty Behind a High-Impact Project
Show what made a high-impact project technically difficult by connecting its constraints, non-obvious mechanism, alternatives, implementation decisions, and evidence of the result.
Behavioral & LeadershipTechnical Screen - AuroraHardMachine Learning EngineerApplying LLMs to Autonomous Driving Despite Hallucination and Real-Time Limits
An open-ended ML system design discussion on how large language models and vision-language models could be used in autonomous driving, including whether one could actually drive the vehicle. It tests mapping off-board and on-vehicle uses, containing hallucination and latency in a safety-critical stack, and planning evaluation.
ML System DesignTechnical Screen - AuroraMediumSoftware EngineerCompute streaming sliding-window minimums
This question evaluates a candidate's understanding of streaming algorithms and efficient data-structure techniques for maintaining sliding-window minima, measuring competency in algorithmic thinking, time and space complexity, and online processing.
Coding & AlgorithmsTechnical Screen - AuroraMediumSoftware EngineerEvaluate an Arithmetic Expression
Evaluate arithmetic expressions containing non-negative integers and the four basic operators without using eval. Preserve precedence and left associativity, implement division that truncates toward zero, and process expressions up to 300,000 characters efficiently.
Coding & AlgorithmsTechnical Screen - AuroraHardSoftware EngineerImplement a reference-counted smart pointer
This question evaluates understanding of C++ resource management, ownership semantics, RAII, and reference counting implementation within the coding and algorithms domain, emphasizing pointer semantics and object lifetime.
Coding & AlgorithmsTechnical Screen - AuroraHardMachine Learning EngineerPitching an LLM-for-Autonomy Initiative to Leadership to Win Scope
A leadership question asking how you would present an initiative to bring language models into a self-driving program to leadership and win scope for it. It tests problem framing, gathering evidence, handling risk in a safety-critical organization, aligning stakeholders, and making a concrete, phased ask.
Behavioral & LeadershipTechnical Screen - AutodeskMediumSoftware EngineerDesign a Real-Time Multi-Source Change Data Pipeline
Design a low-latency CDC pipeline that joins multiple databases, propagates updates and deletes, recovers state, and maintains a queryable output dataset.
System DesignOnsite - AutodeskMediumMachine Learning EngineerExplain 3D geometry data
Explain 3D geometry data 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 - AxonMediumSoftware EngineerAnswer tough self-awareness and team questions
This question evaluates self-awareness, maturity, and interpersonal leadership competencies within the Behavioral & Leadership domain, focusing on the ability to acknowledge misunderstandings about oneself and to articulate team shortcomings without defensiveness.
Behavioral & LeadershipOnsite - AxonMediumSoftware EngineerDesign Reliable Upload and Download for Very Large Files
Design resumable upload and range-based download for files too large to transfer reliably in one request. Cover chunk identity, integrity hashes, idempotent completion, authorization, committed-file visibility, object-storage layout, and cleanup of abandoned sessions.
System DesignTechnical Screen - AxonHardSoftware EngineerDesign a Nearest-Timestamp Status Record Service
Design a high-throughput time-series ingestion and query service that handles out-of-order, duplicate officer telemetry and returns the record closest in time to a requested query timestamp.
System DesignTechnical Screensystem-designtime-seriesdistributed-systems - AxonMediumSoftware EngineerDesign a Test Orchestration System
This question evaluates system design and backend engineering competencies, including distributed orchestration, scheduling, scalability, reliability, operational monitoring, API design, and data modeling for a test orchestration service; it is categorized under System Design and related domains such as distributed systems and CI/CD platforms.
System DesignTechnical Screen - AxonHardSoftware EngineerDesign a tamper-evident video chain-of-custody audit system
Design a tamper-evident video chain-of-custody audit system evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - AxonHardSoftware EngineerDesign an airline booking system
This question evaluates a candidate's ability to design scalable, consistent, and resilient distributed systems for transactional domains, emphasizing API design, data modeling, concurrency control, idempotency, seat inventory guarantees, and external integrations like payments and ticketing.
System DesignTechnical Screen - AxonHardSoftware EngineerDesign an e-commerce analytics warehouse
The question evaluates data engineering and analytics competencies including event schema design, session and identity stitching, dimensional modeling, ingestion pipelines, and operational concerns such as deduplication, partitioning, and handling late or out‑of‑order events.
Analytics & ExperimentationTechnical Screen - AxonMediumSoftware EngineerDesign an image-to-multilanguage translator
This question tests the ability to design a distributed, scalable image processing pipeline that integrates OCR with translation services while addressing latency, storage, and reliability concerns.
System DesignTechnical ScreenDistributed SystemsScalabilityAsynchronous Processing - AxonMediumSoftware EngineerDesign analytical tracking database
This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design analytical tracking database states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - AxonMediumSoftware EngineerDesign body camera checkout system
Design an in-memory inventory management system for body-worn cameras that supports O(1) registration, uniform random checkout, and checkin operations.
Coding & AlgorithmsOnsiteData StructuresHash TableRandomized Algorithms - AxonMediumSoftware EngineerDesign camera-footage upload with custody chain
This question evaluates a candidate's ability to design resilient, secure large-file ingestion systems with integrity verification, resumable chunked uploads, malware and file-type scanning, and an auditable tamper-evident chain of custody, commonly asked to assess architectural thinking about reliability, security, and compliance for evidentiary data. It is in the System Design domain (storage, APIs, background processing, and audit logging) and tests practical application of architectural trade-offs, failure-mode reasoning, and operational concerns rather than only theoretical concepts.
System DesignTechnical Screen - AxonMediumSoftware EngineerDesign fulfillment truck routing and inventory system
This question evaluates architectural design skills for scalable, event-driven fulfillment systems, including competencies in inventory/container state tracking, high-throughput event processing, transactional dock-door scheduling, and vehicle routing optimization; domain: system design.
System DesignTechnical Screen - AxonMediumSoftware EngineerExplain What Motivates and Demotivates You at Work
Explain what consistently motivates and demotivates you at work through one concrete example of each. Connect the conditions to observable behavior, show how you respond constructively when motivation drops, and relate the answer to the environment where you perform well.
Behavioral & LeadershipTechnical Screen - AxonMediumSoftware EngineerExplain scope and impact under pressure
This question evaluates a software engineer's ability to articulate project scope, ownership, trade-offs, measurable impact, and promotion rationale under pressure, assessing leadership, communication, and accountability competencies.
Behavioral & LeadershipTechnical Screen
Attentive
Aurora
Axon