Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for recommendation system to provide the most stable and best experience for our TikTok users. We cover almost all short-text recommendation scenarios in TikTok, such as search suggestions, the video-related search bar, and comment entities.
Requirements
- Design and implement a reasonable offline data architecture for large-scale recommendation systems
- Design and implement flexible, scalable, stable and high-performance storage and computing systems
- Trouble-shooting of the production system, design and implement the necessary mechanisms and tools to ensure the stability of the overall operation of the production system
- Build industry-leading distributed systems such as storage and computing to provide reliable infrastructure for massive date and large-scale business systems
- Develop and implement techniques and analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualisation software
- Applying data mining, data modelling, natural language processing, and machine learning to extract and analyse information from large structured and unstructured datasets
- Visualise, interpret, and report data findings and may create dynamic data reports as well