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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 3901–3930 of 4616 results
- StripeMediumSoftware EngineerDebug Three Planted Bugs in the Mako Python Template Engine
A bug-squash exercise on a copy of the Mako Python template engine with planted bugs: lambda parameters vanish from regenerated code, a directory is mistaken for a template during lookup, and a comment-only control block fails to compile. It tests tracing failures through a template compiler, minimal library fixes and regression tests.
Software Engineering FundamentalsTechnical Screen - StripeMediumSoftware EngineerDebug a POST With a Stream Body That Hangs After a 307 Redirect in Python Requests
A debugging exercise in the Python Requests library: a POST with a file-like body hangs after a 307 Temporary Redirect until the client times out. It tests reasoning about the bytes on the wire, HTTP redirect semantics, stream state across a re-sent request, and writing a deterministic regression test.
Software Engineering FundamentalsTechnical Screen - StripeMediumSoftware EngineerDebug a Tag Validator: Phantom Nulls, Buried Lists, Null vs Empty
Given a small, working deserialization library with three planted bugs, trace each bad output back to its source, fix it in place, and add a regression test. Tests careful root-causing over quick patching, and recognizing which 'empty' representation should be canonical.
Software Engineering FundamentalsTechnical Screendebuggingpythondata-validation - StripeMediumSoftware EngineerDebug a Toy HTTP Client That Hangs on a Redirected Streaming POST
Find and fix a planted bug in a small hand-rolled Python HTTP client: a POST with a file-like body hangs forever after the server answers with a redirect, while a plain bytes body and a non-redirecting request both work fine.
Software Engineering FundamentalsTechnical Screendebugginghttptesting - StripeHardSoftware EngineerDebug an HTTP Client That Hangs After a 307 Redirect With a Streamed Request Body
A debugging exercise on the Python HTTP library Requests: a POST whose body is a file-like stream hangs until it times out after the server answers 307 Temporary Redirect. It tests redirect semantics, Content-Length framing, how a stream behaves when a request is resent, and regression testing of the fix.
Software Engineering FundamentalsTechnical Screen - StripeMediumSoftware EngineerDebug wrong DOM attributes in unknown framework
This question evaluates a candidate's ability to debug frontend DOM attribute mismatches by understanding framework-specific attribute/prop reflection, template/JSX compilation, SSR/hydration differences, and build-toolchain interactions.
Software Engineering FundamentalsTechnical Screen - StripeMediumSoftware EngineerDescribe adapting quickly to unfamiliar problems
This question evaluates adaptability, rapid learning, prioritization, communication, and leadership under pressure as behavioral competencies in a software engineering context, and is categorized under Behavioral & Leadership.
Behavioral & LeadershipTechnical Screen - StripeHardSoftware EngineerDesign a Feature Flag Service with Percentage Rollouts and Allow/Block Lists
System design question: design a feature flag service, similar in spirit to Amazon's Weblab, that lets teams turn features on or off, roll them out to a percentage of users, and force them on or off with allow and block lists. It probes where flag checks run, how users are assigned consistently, and how changes reach every service safely.
System DesignTechnical Screen - StripeMediumSoftware EngineerDesign a Scalable Idempotent Ledger Service
Design a high-throughput, fault-tolerant double-entry ledger service featuring immutable postings, strict write idempotency, and tunable balance freshness.
System DesignTechnical ScreenDistributed SystemsDatabase DesignFinancial Systems - StripeHardData ScientistDesign a leak-free time-split model
This question evaluates a Data Scientist's competency in time-aware predictive modeling, including label leakage prevention for late-arriving events, temporal cross-validation, feature engineering, model selection (logistic regression vs gradient-boosted trees), calibration and thresholding for costed actions.
Machine LearningTechnical Screen - StripeHardSoftware EngineerDesign a local activity counter service
This question evaluates a candidate's skills in designing large-scale distributed systems, focusing on near-real-time ingestion and aggregation, idempotency/deduplication, time-windowed (tumbling and sliding) analytics, hot-key sharding, storage and backfill strategies, and operational concerns including monitoring and privacy.
System DesignTechnical Screen - StripeMediumSoftware EngineerDesign a subscription email scheduler with changes and renewals
This question evaluates event-driven scheduling, deterministic time-based ordering, stateful account updates for plan changes and renewals, and algorithmic merging of notification streams in the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - StripeHardData ScientistDesign a target‑user prediction system
This question evaluates skills in temporal label definition and leakage prevention, time‑bounded feature engineering (recency/frequency and content affinity), uplift and incremental effect estimation, model selection under class imbalance and budgeted outreach, offline metric design, calibration, fairness constraints, and production validation and monitoring. Common in Machine Learning/Data Science interviews, it is asked to gauge both conceptual understanding of causal and validation issues and practical application skills for deploying a ranked outreach model under capacity constraints, including appropriate cross‑validation and thresholding to map predictive scores to business outcomes.
Machine LearningTechnical Screen - StripeMediumSoftware EngineerDesign an Idempotent Double-Entry Ledger
Design a highly reliable, idempotent double-entry ledger system that guarantees strict consistency, append-only immutability, and supports high-concurrency writes on hot accounts.
System DesignTechnical Screensystem-designfintechdistributed-systems - StripeMediumData ScientistDesign an idempotent SQL ETL for late data
This question evaluates practical skills in idempotent ETL design, deduplication by natural keys, handling late-arriving and out-of-order records, upsert/merge strategies, and SQL-based aggregation for daily metrics.
Data Manipulation (SQL/Python)Technical Screen - StripeHardData ScientistDesign and power an A/B test
This question evaluates a data scientist's competency in experimentation design, including metrics selection and guardrails, statistical power and sample-size calculation, sequential monitoring and ramp strategies, operational checks for randomization and contamination, and choosing credible quasi-experimental alternatives.
Analytics & ExperimentationTechnical Screen - StripeMediumData ScientistDesign metrics and write SQL for a case
This question evaluates the ability to define time‑bounded, attributable conversion metrics and to implement joins, aggregations, and diagnostic checks in SQL to measure marketing outreach impact.
Data Manipulation (SQL/Python)Technical Screen - StripeMediumMachine Learning EngineerDesign payment fraud detection
This question evaluates a candidate's ability to design end-to-end machine learning systems for payment fraud detection, covering competencies in labeling, imbalanced learning, feature engineering across users/merchants/cards/devices/IPs and graph relationships, model selection, online serving, latency and feature freshness, monitoring, experimentation, and adversarial robustness. As an ML System Design problem for a Machine Learning Engineer role, it is commonly asked to probe trade-offs between fraud loss, false positives, user friction and latency and requires both conceptual understanding and practical application of production ML concerns such as evaluation metrics, thresholding, retraining, and operational constraints.
ML System DesignTechnical Screen - StripeMediumSoftware EngineerDesign payment-to-invoice matcher with priorities
This question evaluates parsing and data modeling skills, deterministic matching algorithms with prioritization and tie-breaking, handling monetary values as integer cents, and the ability to design comprehensive test suites for edge cases.
Data Manipulation (SQL/Python)Technical Screen - StripeMediumSoftware EngineerDiscuss self-intro, location, pay, motivation
This Stripe Software Engineer technical-screen question covers the opening conversation: a 60–90 second self-introduction, why-Stripe motivation and alignment, location and remote/time-zone preferences, compensation expectations with rationale, and the questions you should ask about team projects and org stability. It evaluates communication, self-presentation, logistical fit, and compensation transparency rather than coding skill.
Behavioral & LeadershipTechnical Screen - StripeMediumSoftware EngineerEV Charger Registry with Haversine Nearest-Station Routing
Build an in-memory EV charging station registry with status tracking, a haversine distance function, and nearest-online-station routing with deterministic tie-breaks. Tests clean API design, careful spherical math, and corner-case handling.
Software Engineering FundamentalsTechnical Screenclass-designgeometryhaversine - StripeMediumSoftware EngineerEvaluate Ordered Access-Control Rules
Implement an access-control evaluator that parses rule strings with conditions and returns the first matching decision (ACCEPT or BLOCK).
Coding & AlgorithmsTechnical ScreenStringsParsingDesign - StripeMediumData AnalystEvaluate Stripe Capital Loan Performance
This question evaluates a data analyst's competency in product analytics, metric design, cohort and segment analysis, and causal inference for a working-capital loan product.
Analytics & ExperimentationTechnical Screen - StripeHardData ScientistEvaluate a new product with experimentation
This question evaluates experimental design and causal inference skills, including defining an Overall Evaluation Criterion (OEC) and guardrail metrics, selecting an appropriate test design and ramp/power strategy, specifying quasi-experimental fallbacks, and performing metric diagnostics for a recommendation module in a commerce app.
Analytics & ExperimentationTechnical Screen - StripeMediumSoftware EngineerFind linked merchants by shared fields
This question tests the ability to model entity relationships using a graph representation and implement a traversal algorithm to identify connected components based on shared identity fields.
Coding & AlgorithmsTechnical ScreenGraphsHash MapsDisjoint Set Union - StripeMediumSoftware EngineerFind linked user records by similarity
This question evaluates the ability to compute weighted field-based similarity and reason about adjacency relationships in an undirected graph, testing competencies in similarity scoring, record linkage, and basic graph traversal.
Coding & AlgorithmsTechnical Screen - StripeMediumSoftware EngineerFind linked user records by weighted similarity
This problem tests your ability to model relationships as a graph and compute connected components based on weighted similarity scores between user records.
Coding & AlgorithmsTechnical ScreenGraphDSUOptimization - StripeHardSoftware EngineerFix Three Mako Template Bugs: AST Arg Visitor, Directory Lookup, Comment-Only Blocks
A debugging exercise on Mako, the open-source Python template library, with three injected defects: an AST visitor missing its visit_arg method, a template lookup that fails on a directory path, and comment-only control blocks that do not compile. It tests NodeVisitor dispatch, reading generated code, minimal fixes and regression tests.
Software Engineering FundamentalsTechnical Screen - StripeMediumSoftware EngineerFix Three Planted Bugs in a Tiny Python Template Engine
Trace three reported failures in a small template engine to their root causes (a greedy regex, a nesting-unaware block parser and a path-traversal hole), fix each minimally and add regression tests. Tests systematic debugging across tokenizer, parser and loader layers.
Software Engineering FundamentalsTechnical Screendebuggingregexparsing - StripeHardSoftware EngineerGenerate Available 30-Minute Time Slots
This problem tests your ability to manipulate time intervals, handle recurring weekly schedules, and perform intersection logic between availability windows and existing booked appointments.
Coding & AlgorithmsTechnical ScreenIntervalsDatetimeScheduling
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