ML System Design: NLP interview questions

Design a chatbot system that should handle 1000 active users concurrently and respond to queries within 2 seconds. What architecture would you propose and which technologies would you use?

Design a document classification pipeline that should process 1 million documents per week and achieve at least 85% accuracy. What stages would you include in the pipeline and which algorithms would you use?

Design a named entity recognition (NER) system that should process 10,000 texts per day and have a response time of less than 1 second. How will you ensure the scalability and reliability of this system?

Design a search system that should support 500 QPS and provide both semantic and keyword search capabilities. What approach would you take to integrate these two types of search?

Design a text summarization service that should process 100,000 texts per month and return summaries no longer than 150 words. What will be your architecture and technologies?

Design a retrieval-augmented generation (RAG) system that should handle 2000 user queries per hour and provide answer quality of at least 90%. How would you organize the data storage and models?

Design a content moderation system that should process 1 million messages per day and achieve a false positive rate of less than 5%. What strategies and algorithms would you apply?

Design a system for serving large language models (LLM) that supports 100 QPS and has a response time of no more than 500 ms. What technologies and approaches would you use to meet these requirements?

Design an architecture for an NER system that should support 10,000 concurrent users and process 100,000 documents per day. How will you handle latency and scalability?

Design a semantic search system that should handle 5 million documents and provide search results with a latency of less than 200 ms. What are your recommendations for architecture and data storage?

Design a system that handles requests to a chatbot with 10,000 active users simultaneously. Consider a response time of no more than 300 ms and an infrastructure budget of $5,000 per month. What will your architecture look like?

You need to build a document classification system with a data volume of 1 million documents and a processing latency of no more than 1 second. What approach will you take for model training, and what architecture will you propose?

Design a system for named entity recognition from texts with a data volume of 10,000 documents per day. Consider the need to maintain an accuracy of at least 85% and a processing time of no more than 200 ms per document. What technologies will you use?

You need to build a search engine that processes 500 QPS from users and supports both semantic and keyword search. How will you organize data storage and indexing considering a budget of $10,000 per month?

Design a text summarization system that handles 1,000 requests per minute with a maximum latency of 500 ms. What architecture will you propose to ensure quality summaries?

You need to build a system for serving an LLM that will serve 1,000 concurrent users with a latency of no more than 100 ms. What will be your key architectural and scaling considerations?

Design a RAG pipeline that processes 200 QPS and achieves query accuracy of at least 90%. How will you organize the components, and what technologies will you use?

Design a content moderation system for a platform with 5 million users, ensuring content checks with a maximum response time of 1 second and a minimum accuracy of 95%. What approaches and technologies will you apply?

Design a document classification system that needs to process 100,000 documents per day and achieve an accuracy of at least 85%. The system should be designed with scalability in mind to handle up to 1,000,000 documents per day in the future. Please discuss the architecture, data processing approaches, and model selection.

You need to build a chatbot that will serve 10,000 active users concurrently with a response time of less than 2 seconds for each query. The bot should support both natural language conversations and FAQs. Please discuss the necessary system components, their interactions, and approaches to query processing.