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Software Engineer 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 1–5 of 5 results

  • AmazonMediumSoftware Engineer
    Resolve a Conflict Between Metrics and Customer Feedback

    This question tests your ability to troubleshoot conflicting signals in A/B testing and product analytics, requiring a structured approach to reconciling quantitative data with qualitative sentiment.

    Analytics & ExperimentationOnsiteAnalyticsA/B TestingDecision Making
  • AnthropicHardSoftware Engineer
    Design a profiling plan for kernels

    This question evaluates competency in performance profiling, experimental design, microarchitectural analysis, statistical methodology, and kernel-level performance engineering.

    Analytics & ExperimentationOnsite
  • AnthropicHardSoftware Engineer
    How do you design an A/B experiment?

    This problem tests your ability to design a rigorous A/B experiment for a consumer-facing AI product, focusing on identifying interference, selecting appropriate metrics, and addressing statistical validity.

    Analytics & ExperimentationOnsiteA/B TestingExperiment DesignMetrics
  • RobloxHardSoftware Engineer
    Define success metrics and monitoring

    Define success metrics and monitoring evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Analytics & ExperimentationOnsite
  • UberMediumSoftware Engineer
    Define and integrate room ranking factors

    Define and integrate room ranking factors evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Analytics & ExperimentationOnsite