TikTok's Recommendation Architecture Team is responsible for real-time computing direction, handling the design and development of real-time computing systems for TikTok videos, live streams, e-commerce, and a billion-user product recommendation system. Their main focus is ensuring system stability and high availability. They abstract general real-time computing systems, build a unified recommendation feature middleware, and implement a flexible and scalable high-performance storage system and computing model. This enables advanced real-time data systems for deduplication, counting, feature services, and other recommendation-related business needs.
Responsibilities:
- Design and implement real-time (streaming computing) data systems for large-scale recommendation systems.
- Create flexible, scalable, stable, and high-performance storage systems and computing models.
- Troubleshoot production system failures, design and implement necessary mechanisms and tools to ensure overall stability of the production systems
- Construct industry-leading streaming computing frameworks and other distributed systems to provide reliable infrastructure for massive data and large-scale business systems
- Research, design, and develop computer and network software or specialised utility programs.
- Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis.
- Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures.
- Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements.
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