Scalability and Code Organization Questions

Focuses on designing software and codebases that remain maintainable and performant as features and user load grow. Areas include modularity and separation of concerns, component and API boundaries, when and how to refactor, trade offs between monolith and service oriented architectures, data partitioning and caching strategies, performance optimization, testing strategies, dependency management, code review practices, and patterns for maintainability and evolvability. Interview questions may ask candidates to reason about design choices, identify coupling and cohesion issues, and propose practical steps to evolve an existing codebase safely.

MediumTechnical

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What patterns and checks should you use to move experiment code (Jupyter notebooks) into production-ready artifacts? Suggest templates, automated checks, code review requirements, feature flags, and a lightweight staging environment to validate experiments before production push.

HardSystem Design

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You operate many model services running on heterogeneous hardware. Design an autoscaling and scheduling policy that optimizes cost subject to multiple SLOs (latency, throughput, model accuracy). Include model placement, pre-warming strategies, bin-packing rules, priority queues, and handling cold-starts for large models.

EasyTechnical

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Explain separation of concerns in a data science project by defining responsibilities for: data ingestion, feature engineering, model training, model serving, and monitoring. For each component describe a recommended interface (for example, function signature or REST contract) and one reason why separating it improves scalability and team autonomy.

MediumTechnical

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Your pipeline currently performs batch training nightly. Business asks for hourly model updates to react faster. Propose incremental architectural and code changes to safely increase model update frequency while keeping maintainability and testing. Include deployment, monitoring, and budget considerations.

MediumSystem Design

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Design a comprehensive testing strategy for a model-serving microservice: include unit tests, integration tests, contract tests, load tests, chaos tests, and production canary tests. For each test type propose tools, test data generation approaches, and how you would integrate them into CI to gate deployments.

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