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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
- Topics
- 8
- Languages
Showing 3181–3210 of 4616 results
- PalantirMediumSoftware EngineerDiscuss logistics and compensation
Discuss logistics and compensation 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.
Behavioral & LeadershipTechnical Screen - PalantirMediumSoftware EngineerGroup employees by shared interests
This question evaluates a candidate's competency in organizing and querying collections, mapping relationships between entities, and reasoning about algorithmic time and space complexity within data structures and grouping operations.
Coding & AlgorithmsTechnical Screen - PalantirEasySoftware EngineerMerge K Individually Sorted Integer Arrays Into One Sorted Array
Merge k integer arrays, each sorted in non-decreasing order, into one sorted array that keeps every duplicate. The interviewer asked for the two-pointer method and divide and conquer, so the problem tests merging sorted sequences and how the cost grows with the number of arrays.
Coding & AlgorithmsTechnical Screen - PalantirMediumSoftware EngineerReflect on experiences and teamwork
Reflect on experiences and teamwork 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.
Behavioral & LeadershipTechnical Screen - PalantirMediumSoftware EngineerSimulate a Growing Snake on a Grid and Report the Score After Every Move
Simulate a snake moving on a rectangular grid, eating food that appears one piece at a time, and return the score after every move or -1 once the snake leaves the board or runs into itself. It tests precise state simulation, collision rules around the moving tail, and efficient tracking of the snake's body.
Coding & AlgorithmsTechnical Screen - Palo Alto NetworksMediumSoftware EngineerDesign a thread-safe high-QPS rate limiter
A Palo Alto Networks system-design screen: design and implement a thread-safe, high-QPS rate limiter that enforces per-identity request quotas. The answer covers algorithm choice (token bucket vs. fixed/sliding window), atomic per-key state with locks or CAS, hot-path performance, bounded-memory eviction, distributed scaling (Redis+Lua, token leasing, consistent-hash partitioning), and rejection semantics.
System DesignTechnical Screen - Palo Alto NetworksMediumSoftware EngineerFind minimum tanks to cover all houses
This question evaluates a candidate's proficiency in algorithm design, specifically greedy strategies and string/array manipulation for coverage and optimization under local adjacency constraints.
Coding & AlgorithmsTechnical Screen - ParadromicsMediumSoftware EngineerCompare RDBMS vs NoSQL and containers
Evaluates mastery of data storage and scaling trade-offs (RDBMS vs NoSQL), virtualization and containerization concepts (VMs, Docker), orchestration features (Kubernetes), and language-level performance optimization (Python vs C++).
Software Engineering FundamentalsTechnical Screen - ParadromicsMediumSoftware EngineerCompute ways to climb n steps
This Coding & Algorithms question evaluates recursion and dynamic programming concepts by asking for the count of distinct ways to climb n steps, framed at an algorithmic/implementation level. It is commonly asked because it probes recognition of overlapping subproblems and the ability to optimize naive recursive approaches through subproblem reuse and improved time/space efficiency.
Coding & AlgorithmsTechnical Screen - ParadromicsMediumSoftware EngineerImplement a hash table with put/get
This question evaluates implementation and design skills for hash-based data structures, testing competency in data structures, hashing, collision handling, and achieving expected O(1) put/get performance in the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - Paramount CommerceHardSoftware EngineerDesign a Go music player with playlists
This question evaluates object-oriented system design, API and data-structure modeling, state and concurrency management, persistence considerations, and algorithmic time/space complexity within a Go-based music player domain.
System DesignTechnical Screen - Paramount CommerceMediumSoftware EngineerExplain motivations and company fit
This question evaluates motivation, cultural and team fit, adaptability, and the ability to handle ambiguity while aligning technical work with business goals.
Behavioral & LeadershipTechnical Screen - PatreonMediumSoftware EngineerAnalyze Reports in a Nested Org Chart
This problem tests your ability to model hierarchical tree structures and use post-order traversal to aggregate data across deep organizational levels efficiently.
Coding & AlgorithmsTechnical ScreenTreesGraphsRecursion - PatreonEasyData EngineerDesign a Data Processing System for JSON User Records: Batch vs Streaming Input
Design a data processing system for JSON user records that contain names, addresses and payment methods, and explain how the design changes when the upstream source delivers data in batches versus as a continuous stream. It tests pipeline architecture, idempotent loading, ordering and late data, and the handling of sensitive fields.
System DesignTechnical Screen - PatreonEasySoftware EngineerDesign org chart lookup with preprocessing
This question evaluates skills in data structures and algorithms, specifically tree/forest representation, aggregation of subtree metrics, dynamic updates, and rigorous time and space complexity analysis.
Coding & AlgorithmsTechnical Screen - PayPalMediumSoftware EngineerAssess HashMap vs ConcurrentHashMap
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Assess HashMap vs ConcurrentHashMap states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - PayPalHardData ScientistBuild a real-time ATO model
This question assesses the ability to design an end-to-end, low-latency machine learning pipeline for detecting account takeover (ATO) in payment transactions, focusing on label noise, feature engineering, and system deployment constraints.
Machine LearningTechnical ScreenReal-time SystemsFraud DetectionFeature Engineering - PayPalMediumSoftware EngineerCompare final, finally, finalize
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Compare final, finally, finalize states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - PayPalMediumSoftware EngineerCompare write-back vs write-through caches
This question evaluates understanding of caching policies and memory/storage hierarchy trade-offs, focusing on how write-back and write-through handle writes, coherence, durability, latency, bandwidth, dirty bits, write amplification, and power-loss risks.
Coding & AlgorithmsTechnical Screen - PayPalHardData ScientistCompute Variance from a Python List
This question evaluates understanding of basic statistical concepts and numerical computation—specifically population versus sample variance—and tests algorithmic implementation skills, edge-case handling, and complexity reasoning within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - PayPalEasyData ScientistCompute variance of a list in Python
This question evaluates understanding of statistical measures and numeric computation, focusing on implementing variance calculations (population vs sample) and considerations for numerical stability.
Coding & AlgorithmsTechnical Screen - PayPalMediumSoftware EngineerContrast TCP vs UDP; detect loss
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Contrast TCP vs UDP; detect loss states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - PayPalHardData ScientistDesign an A/B for ATO rule
This question evaluates a data scientist's experiment-design and statistical-analysis competencies, including cluster-aware randomization, power/sample-size calculation, sequential monitoring, and translating detectable effects into net business impact for a real-time account-takeover prevention rule on a payment platform.
Analytics & ExperimentationTechnical Screen - PayPalEasyData ScientistDesign and evaluate a fraud detection strategy
This problem tests your ability to design a holistic fraud detection strategy by balancing technical model metrics with business-critical operational trade-offs.
Analytics & ExperimentationTechnical ScreenFraud DetectionClassificationMetrics - PayPalMediumSoftware EngineerDetect memory leaks in C++
This interview question evaluates engineering fundamentals, trade-offs, examples, pitfalls, and operational implications in a realistic interview setting. A strong answer for Detect memory leaks in C++ states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Software Engineering FundamentalsTechnical Screen - PayPalMediumSoftware EngineerExplain HashMap internals and collisions
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Explain HashMap internals and collisions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - PayPalMediumSoftware EngineerExplain Java volatile semantics
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Explain Java volatile semantics states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - PayPalHardData ScientistExplain differences between Python list and tuple
Evaluates understanding of Python data structures—specifically lists versus tuples—by probing concepts such as mutability and its implications, high-level performance and memory trade-offs, typical use cases, and hashability for use as dictionary keys.
Coding & AlgorithmsTechnical Screen - PayPalMediumSoftware EngineerFind k most frequent in linear time
This question evaluates a candidate's ability to design and analyze efficient frequency-counting algorithms and related data structures, testing competencies in hashing, bucket-based grouping, heap usage, and time/space complexity reasoning.
Coding & AlgorithmsTechnical Screen - PayPalEasyData ScientistHow to evaluate a new homepage feature
A PayPal data science technical screen on designing an A/B test to evaluate a new homepage feature. It covers experiment design and randomization, primary/secondary/guardrail metric selection with tradeoffs, sample-size and power estimation, and pitfalls like novelty effects and interference. The solution emphasizes value-aligned metrics (payment completion over CTR) and fraud guardrails specific to a payments product.
Analytics & ExperimentationTechnical Screen
Palantir
Palo Alto Networks
PayPal