Real-Time Recommendation Engine for Streaming Platform

Design a scalable Python recommendation system using pandas and scikit-learn that generates personalized content suggestions for a streaming service. Implement collaborative filtering with hybrid machine learning techniques that can process 100,000+ user interactions per minute. Include performance optimization strategies, handle cold-start problems for new users, and create a modular architecture that supports multiple recommendation algorithms.