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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 8491–8520 of 9403 results
- TikTokMediumSoftware EngineerSolve array and tree algorithm challenges
This question evaluates algorithmic problem-solving skills across array, heap, and tree data structures, testing competencies in duplicate handling, frequency aggregation, and balancing root-to-leaf path sums within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - TikTokMediumSoftware EngineerSolve common string/DP/stack problems
This problem tests your ability to identify and implement an efficient solution for finding the longest substring that satisfies specific constraints, requiring a sliding window approach.
Coding & AlgorithmsTechnical ScreenSliding WindowHash MapStrings - TikTokHardSoftware EngineerSolve four OA algorithm problems
This problem tests your ability to optimize string manipulation using greedy approaches and Fenwick trees to count minimum adjacent swaps required to transform a string into a palindrome.
Coding & AlgorithmsTechnical ScreenGreedyStringsTwo Pointers - TikTokMediumSoftware EngineerSolve four algorithm design tasks
This multi-part question evaluates algorithm design and data-structure competencies including wildcard string pattern matching and trade-offs between dynamic programming and greedy strategies, dynamic pair-sum maintenance under frequent updates, O(1) LRU cache design, and scheduling/ordering for time-constrained threat neutralization.
Coding & AlgorithmsOnline Assessment - TikTokMediumSoftware EngineerSolve intervals and distinct islands
This question evaluates skills in interval manipulation and identification of distinct connected components in grids, testing competencies in data structure usage, algorithmic reasoning, and spatial pattern recognition within the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - TikTokMediumSoftware EngineerSolve linked list, string filtering, and puzzle
This problem tests your ability to manipulate linked list pointers in-place, apply conditional string filtering with index tracking, and solve a greedy resource partitioning puzzle.
Coding & AlgorithmsTechnical ScreenLinked ListStringsGreedy - TikTokMediumSoftware EngineerSolve message splitting and board crushing
These problems evaluate string manipulation and numeric reasoning for variable-length metadata alongside grid simulation with pattern detection and gravity effects, testing skills such as careful edge-case handling, iterative state updates, and complexity analysis.
Coding & AlgorithmsTechnical Screen - TikTokMediumSoftware EngineerSolve three algorithm tasks
This multi-part question evaluates algorithmic problem-solving across string processing (text justification), handling ambiguous state in sequence validation (parentheses with wildcards), and grid graph traversal with path reconstruction, testing competencies in formatting and spacing logic, state-tracking for correctness under uncertainty, and shortest-path search and reconstruction. It is commonly asked in Coding & Algorithms interviews to assess correctness under edge cases, ability to reason about trade-offs and invariants, and the analysis of time and space complexity, requiring both conceptual understanding and practical implementation skills.
Coding & AlgorithmsTechnical Screen - TikTokHardSoftware EngineerSolve three string/stack/backtracking problems
This problem tests your ability to use a monotonic stack to determine visibility in a 2D line and backtracking to generate valid structural sequences.
Coding & AlgorithmsTechnical ScreenMonotonic StackBacktrackingRecursion - TikTokMediumSoftware EngineerSolve top-K and string rotation match
Solve top-K and string rotation match evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - TikTokHardData ScientistTest 15s to 60s video length change
This question evaluates a data scientist's competency in experimental design, causal inference, metric definition and instrumentation, power/MDE calculations, interference and contamination handling on multi‑sided platforms, and rollout planning.
Analytics & ExperimentationOnsite - TikTokEasyData ScientistTest Billboard Campaign Conversion Rate Exceeds 60%
Evaluates one-sample proportion testing for a billboard conversion rate with 65 conversions out of 100 users. Strong answers state one-sided hypotheses, compute the standard error and confidence interval, run the correct z test against 60%, and interpret why statistical evidence may be insufficient.
Statistics & MathOnsite - TikTokHardProduct ManagerTikTok Product Strategy & Case Design
Practice TikTok PM product decision-making across feature selection, prioritization, Stories strategy, and VR app store design. The solution covers strategy, user problems, RICE-style prioritization, TikTok-native ephemeral content trade-offs, MVP metrics, and immersive VR discovery, safety, and developer tooling.
Product / Decision MakingOther - TikTokEasySoftware EngineerTrace Source Code to an Executable
This question tests the candidate's understanding of the C/C++ compilation pipeline, focusing on how source code is transformed into a runnable binary and the role of different build artifacts.
Software Engineering FundamentalsTechnical ScreenCompilationLinkingToolchain - TikTokHardData ScientistUse DiD for staggered treatment adoption
This question evaluates proficiency in causal inference for panel data, specifically difference-in-differences with staggered adoption, heterogeneous and dynamic treatment effects, event-study design, pre-trend diagnostics, cluster-robust inference, and comparison with propensity-score matching.
Statistics & MathTechnical Screen - TikTokMediumSoftware EngineerWalk through resume and resolve conflicts
Walk through resume and resolve conflicts 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 - TikTokHardMachine Learning EngineerWalk through resume under pressure and critique
A TikTok machine-learning-engineer onsite behavioral & leadership question: walk through four resume projects — problem and constraints, your ownership, architecture and key decisions, alternatives and trade-offs, measurable outcomes, and the hardest challenge — then defend your trade-offs under pushback, respond to blunt feedback, and adapt your communication to a different language or style. It evaluates technical ownership, systems thinking, experimental rigor, and composed, data-first communication under pressure.
Behavioral & LeadershipOnsite - TikTokEasyData ScientistWhen prioritize precision vs recall
This question evaluates a data scientist's competency with binary classification metrics (precision and recall), cost-sensitive decision-making, and operating-threshold selection for productized models in the Machine Learning domain.
Machine LearningTechnical Screen - TikTokMediumData ScientistWrite SQL for 7-day geo-localized revenue dashboard
This question evaluates SQL skills in time-zone aware local-date aggregation, idempotent event deduplication, cohorting for new versus returning users, calculation of revenue and conversion metrics, and anomaly detection via median-based drop flags.
Data Manipulation (SQL/Python)HR Screen - TikTokEasyData ScientistWrite SQL for TikTok Live creator metrics
This question evaluates SQL data-manipulation competencies such as joins, aggregations, group-by and window functions, handling missing activity rows, date-range filtering, country partitioning, and deterministic tie-breaking for top-k metrics.
Data Manipulation (SQL/Python)Technical Screen - TikTokMediumData ScientistWrite SQL for geo posting-frequency drops
This question evaluates proficiency in SQL-based time-series data manipulation, including time zone–aware date normalization, window functions, aggregation, filtering and median computations within the Data Manipulation (SQL/Python) domain.
Data Manipulation (SQL/Python)Onsite - TikTokMediumData ScientistWrite SQL for last-7-day metrics without windows
This question evaluates proficiency in ANSI SQL data manipulation, including aggregation, de-duplication, date arithmetic, joins and subqueries, GROUP BY/HAVING usage, and cohort/retention and conversion calculations performed without window functions.
Data Manipulation (SQL/Python)Technical Screen - TikTokMediumSoftware EngineerWrite complex SQL for cohorts and retention
This question evaluates advanced SQL and data-engineering competencies such as cohort and retention analysis, deduplication, timezone normalization, last-touch attribution, aggregate revenue calculations, and effective use of window functions in the Data Manipulation (SQL/Python) domain.
Data Manipulation (SQL/Python)Technical Screen - TinderHardProduct ManagerProfile Customization for Millennials & Gen Z
Practice designing a Tinder profile-customization feature for Millennials and Gen Z without slowing the swipe experience. The solution proposes modular Profile Layers, explains cohort needs, safety and moderation constraints, research validation, launch sequencing, and metrics for match quality, conversations, retention, and guardrails.
Product / Decision MakingOnsite - TmlMediumSoftware EngineerImplement a Resizable Deque
This question evaluates proficiency in data structures and array-based implementations, specifically building a resizable double-ended queue (deque) backed by a circular array and understanding amortized O(1) operation costs.
Coding & AlgorithmsTechnical Screen - ToastHardSoftware EngineerCode Review of a Multi-File HTTP API: Wrong Method, Payload and Validation Bugs
A code-review exercise on several files that implement an HTTP API, where the known defects include a GET endpoint that should be POST, a request payload problem and missing input validation. It tests explaining each defect by its impact, fixing it consistently across files, and running a prioritized review within an hour.
Software Engineering FundamentalsTechnical Screen - ToastHardSoftware EngineerDesign a Restaurant Seat and Table Reservation System
A system design question asking for a restaurant seat reservation system in which diners search availability by party size and time, then book, change or cancel. It tests the table-and-time inventory model, preventing double booking under concurrent requests, holds, availability caching and partitioning by restaurant.
System DesignTechnical Screen - Together AIHardSoftware EngineerDesign a GPU-aware pod scheduler
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 a GPU-aware pod scheduler states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - Together AIMediumSoftware EngineerDetect cycles and break them in pod dependencies
This question evaluates proficiency with directed graph concepts and dependency resolution, focusing on cycle detection and selecting a single dependency edge whose removal renders the graph acyclic.
Coding & AlgorithmsTechnical Screen - Together AIEasySoftware EngineerDiagnose CPU Performance Problems on a Linux Server
Diagnose Linux CPU slowness from host and thread metrics through scheduling, limits, profiles, and a workload-linked verification of the bottleneck.
Software Engineering FundamentalsTechnical Screen
TikTok
Together AI