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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
- Companies
- 11
- Topics
- 8
- Languages
Showing 721–750 of 4616 results
- 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 - 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 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 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 - AxonMediumSoftware EngineerExplain your career path and leadership impact
This question evaluates leadership, people management, technical judgment, product/mission alignment, metrics-driven impact, cross-team collaboration, mentoring, and operational decision-making competencies relevant to engineering manager and tech lead roles.
Behavioral & LeadershipTechnical Screen - BCGMediumForward Deploy EngineerShortest Distance in an Unweighted Adjacency-Matrix Graph
This problem tests implementing breadth-first search (BFS) on an unweighted, undirected graph represented as an adjacency matrix to find the shortest path distance between two vertices.
Coding & AlgorithmsTechnical ScreenGraphBFSShortest Path - Bank of AmericaMediumData ScientistDescribe initiative, project, analysis, and relationship-building
This set of behavioral and leadership questions evaluates initiative, quantitative and technical project execution, complex problem-solving, and relationship-building competencies relevant to a Data Scientist role within the Behavioral & Leadership domain.
Behavioral & LeadershipTechnical Screen - Bank of AmericaMediumData ScientistDiscuss a Recent Financial-Market Trend
Tests your ability to formulate and rigorously analyze a recent financial-market trend by decomposing asset value changes versus net organic investor flows, designing econometric hypothesis tests, and evaluating data limitations.
Analytics & ExperimentationTechnical ScreenFinancial AnalyticsTime SeriesHypothesis Testing - Bank of AmericaMediumData ScientistExplain core probability and ML statistics concepts
This question evaluates core probability and machine learning statistics competencies including probability basics, descriptive statistics, correlation versus independence, linear regression and regularization, and dimensionality reduction (PCA), falling under the Machine Learning domain for Data Scientist roles and testing both conceptual understanding and practical application. Such multi-part theory questions are commonly asked to probe understanding of fundamental statistical concepts and modeling assumptions, ensuring the candidate can reason about uncertainty, estimator properties, multicollinearity, and eigenstructure without relying solely on implementation details.
Machine LearningTechnical Screen - Bank of AmericaMediumData ScientistShow Initiative, Analytical Judgment, and Relationship Building
This question assesses a candidate's ability to articulate professional narratives that demonstrate self-driven impact, rigorous problem-solving, and interpersonal collaboration skills.
Behavioral & LeadershipTechnical ScreenBehavioralCommunicationProblem-solving - BasetenHardSoftware EngineerBuild a Crash-Consistent Single-Server Key-Value Store
Design and implement a thread-safe, crash-consistent key-value storage engine that persists byte-string records to an append-only log on disk, recovers from partial writes, and supports tombstones.
Software Engineering FundamentalsTechnical Screensystems-programmingstorage-enginecrash-consistency - BasetenMediumData EngineerDesign a Data Pipeline for Messy Pod Alerts and Bad Pod Detection
Prepare for a Baseten system design interview about design a data pipeline for messy pod alerts and bad pod detection. This question focuses on requirements, architecture, trade-offs, reliability, and follow-up discussion areas.
System DesignTechnical Screen - BasetenHardSoftware EngineerDesign an LLM Inference Serving System
Design an end-to-end, high-performance LLM serving platform that manages request admission, continuous batching, KV cache memory, token streaming, and GPU fleet autoscaling under tight latency SLAs.
ML System DesignTechnical Screenml-system-designllm-servingdistributed-systems - BasetenHardSoftware EngineerParallelize Blocking API Calls with a Thread Pool
Implement a robust, bounded concurrent batch runner that parallelizes blocking calls while preserving input order, handling errors, and enforcing timeouts.
Software Engineering FundamentalsTechnical ScreenConcurrencyPythonMultithreading
Aurora
Axon
Bank of America
Baseten