Meta interview questions

Showing 541–570 of 666 results

• Remove runs of length at least kMedium

  This question evaluates string manipulation, run-length detection, and algorithmic efficiency, focusing on tracking and removing maximal contiguous character groups. It is commonly asked in the Coding & Algorithms domain to assess practical application–level skills in designing linear-time, linear-space implementations that handle dynamic sequence collapses using appropriate data structures.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Replace legacy ads model safelyHard

  This question evaluates competence in machine learning systems engineering, including offline validation, counterfactual/off‑policy evaluation, online experimentation design, and production monitoring for ad-ranking models.

  MetaData ScientistMachine LearningOnsite
• Resolve Ambiguous Requirements Before BuildingHard

  Tests your ability to drive clarity and make responsible engineering progress when assigned a critical project with underspecified or conflicting requirements.

  MetaSoftware EngineerBehavioral & LeadershipOnsite
• Resolve Conflicts and Convince Skeptical Stakeholders EffectivelyMedium

  This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Resolve Conflicts and Convince Skeptical Stakeholders Effectively states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  MetaData ScientistBehavioral & LeadershipOnsite
• Resolve Team Conflicts and Exceed Job Expectations SuccessfullyMedium

  Evaluates behavioral interview readiness for initiative beyond formal responsibilities and team conflict resolution. Strong answers use STAR, explain why the candidate stepped in, show stakeholder management, quantify impact, and resolve conflict without blame.

  MetaData ScientistBehavioral & LeadershipTechnical Screen
• Resolve Ties for Top-10 Users in SQL QueryMedium

  This question evaluates proficiency in SQL ranking and tie-resolution techniques for generating deterministic top-N leaderboards, focusing on handling identical scores while producing an exact set of rows.

  MetaData ScientistData Manipulation (SQL/Python)Onsite
• Resolve a cd Path Against the Current DirectoryMedium

  Implement simplified Unix-style cd path resolution for absolute and relative inputs containing repeated separators, dot components, and parent-directory steps. The challenge focuses on component semantics, root boundaries, empty arguments, exact normalization, and linear processing of long paths without filesystem lookups.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Resolve cross-team conflict and align incentivesMedium

  This question evaluates a Data Scientist's ability to resolve cross-team conflicts through stakeholder mapping, incentive alignment, quantified negotiation planning, meeting facilitation, escalation management, and success measurement.

  MetaData ScientistBehavioral & LeadershipOnsite
• Resolve exclusion, learn fast, and manage conflictHard

  This question evaluates interpersonal leadership, cross-team collaboration, conflict resolution, rapid domain learning, stakeholder mapping, and the ability to quantify analytic trade-offs and impact within a data science context.

  MetaData ScientistBehavioral & LeadershipOnsite
• Resolve teammate feeling unwelcome with measurable stepsHard

  This question evaluates leadership competencies in managing psychological safety, conflict resolution, confidentiality, remote-team dynamics, evidence gathering, documentation, escalation, and outcome measurement.

  MetaData ScientistBehavioral & LeadershipOnsite
• Respond to Critical Feedback and Show the ChangeHard

  This question assesses a candidate's ability to handle constructive criticism professionally, their capacity for self-reflection, and their demonstrated commitment to measurable professional growth.

  MetaSoftware EngineerBehavioral & LeadershipOnsite
• Retrieve Ad Metrics and Rates for Last 7 DaysMedium

  This question evaluates proficiency in SQL-based data manipulation including joins, conditional aggregation, time-based filtering, and computation of advertising metrics such as impressions, clicks, CTR, and conversion rate.

  MetaData ScientistData Manipulation (SQL/Python)Onsite
• Retrieve Top Five Ads by Conversions in 30 DaysMedium

  This question evaluates a candidate's competency in SQL data manipulation, specifically aggregating event data and applying time-window filters to produce ranked metrics.

  MetaData ScientistData Manipulation (SQL/Python)Onsite
• Return a Shortest Path Through a Binary GridMedium

  Implement breadth-first search on an 8-directional binary grid to find and reconstruct a deterministic shortest path from the top-left to the bottom-right cell.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Return all root-to-leaf path sumsMedium

  This question evaluates competency in binary tree traversal and path-state accumulation, focusing on the ability to compute sums along root-to-leaf paths while handling edge cases like empty trees and negative values.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Return count and renewal percentage of unreturned good copiesMedium

  This question evaluates proficiency in SQL data manipulation, including conditional filtering, NULL handling, aggregation, and computing conditional percentages across related tables.

  MetaData EngineerData Manipulation (SQL/Python)Technical Screen
• Return right and left side views of a treeMedium

  This problem tests your ability to perform level-order traversal on a binary tree and manipulate the results to extract the boundary nodes.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Return the Minimum-Sum Root-to-Leaf PathHard

  Tests tree traversal, path reconstruction, tie-breaking logic, and handling deeply skewed trees with up to 100,000 nodes without exceeding recursion depth limits.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Return top-3 content per categoryMedium

  This question evaluates the ability to perform grouped top-k selection, deterministic tie-breaking and ordering, and to reason about algorithmic efficiency when manipulating structured datasets in the Data Manipulation (SQL/Python) domain for a Data Engineer role.

  MetaData EngineerData Manipulation (SQL/Python)Onsite
• Reverse between equal-value nodes in listMedium

  This question evaluates a candidate's ability to manipulate singly linked lists, perform in-place sublist reversal, and manage pointer references and node boundaries.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Reverse sublist between equal-value nodesMedium

  This question evaluates linked-list manipulation and pointer-management skills, focusing on reversing an in-place sublist between two nodes with equal values while respecting O(n) time and O(1) extra space constraints.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Root-Causing an Instagram Satisfaction Decline During Ad Monetization GrowthMedium

  A Meta product manager interview question about Instagram, where ad revenue has risen while user satisfaction has fallen. It tests validating both metrics, decomposing revenue and satisfaction to find a shared cause, testing hypotheses with holdouts, and weighing short-term revenue against long-term user health.

  MetaProduct ManagerAnalytics & ExperimentationOther
• Run a clean A/B test for recommendationsMedium

  This question evaluates a data scientist's competency in experimental design, causal inference, and statistical power analysis for A/B tests, covering randomization unit choice, contamination prevention, metric and guardrail selection, clustering adjustments, and bias-control techniques.

  MetaData ScientistAnalytics & ExperimentationOnsite
• Scale a Cache or Rate Limiter Across Multiple MachinesMedium

  Tests your ability to design a horizontally scalable distributed rate limiter and caching layer, focusing on data partitioning, hot-key mitigation, failure modes, and consistency trade-offs.

  MetaSoftware EngineerSystem DesignOnsite
• Select and prioritize metrics with guardrailsMedium

  This question evaluates a candidate's ability to design a robust metrics framework for product experiments, covering selection and normalization of success metrics, feature-only sizing and ecosystem metrics, explicit cannibalization reads, guardrails, multiple-testing control, and back-of-the-envelope LTV/ARPDAU impact estimation.

  MetaData ScientistAnalytics & ExperimentationTechnical Screen
• Select words to maximize unique charactersMedium

  This question evaluates understanding of combinatorial search and string manipulation, specifically the ability to reason about unique-character constraints, subset selection, and set-like representations.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Self-Attention: Implementation, Complexity, and Efficient VariantsHard

  Tests a candidate's mathematical and practical grasp of scaled dot-product attention, its computational and memory bottlenecks, and modern algorithmic optimizations like FlashAttention and linear attention.

  MetaMachine Learning EngineerMachine LearningOnsite
• Set up a Python interview environmentMedium

  This question evaluates proficiency in Python development environment setup, including dependency and virtual environment management, secure handling of environment variables for secrets, tooling for rapid feedback, reproducibility practices, and basic service scaffolding.

  MetaSoftware EngineerData Manipulation (SQL/Python)Onsite
• Share different perspective from leadership feedbackMedium

  This question evaluates a software engineer's ability to receive and integrate leadership feedback, measuring competencies such as adaptability, self-awareness, communication, and accountability.

  MetaSoftware EngineerBehavioral & LeadershipOnsite
• Should We Launch Group Calling?Hard

  A Meta Data Scientist technical-screen case: using only one-to-one call logs, decide whether to build a group calling feature and how to measure a launch's success. It tests product analytics, proxy-metric design, network analysis, causal inference, and experiment design under social-network interference.

  MetaData ScientistAnalytics & ExperimentationTechnical Screen