FastQA

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How do you manage the deployment and versioning of machine learning models in a production environment?
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What strategies do you use to ensure data consistency in distributed systems?
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How do you stay updated with the latest backend technology trends?
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How do you handle inter-service communication in a microservices architecture using gRPC, REST, and message queues?
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What is idempotency and why is it important in API design?
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What is your experience with Azure and AWS, and how do they compare?
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How can versioning be managed in REST APIs?
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What are the best practices for serving AI models in a REST API?
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Can you explain Python's Global Interpreter Lock (GIL) and its impact on concurrency?
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How can you optimize the performance of AI model inference in backend services?
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How do you ensure backend systems comply with regulations such as GDPR and PCI-DSS?
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How do you manage real-time inference versus batch processing in an AI system?
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