The Recommendation Architecture Team is responsible for designing and developing recommendation system architectures for various products under the company. We ensure system stability and high availability, optimize performance for online services and offline data pipelines, address system bottlenecks, and reduce operational costs. We also abstract reusable system components and services to build recommendation and data middleware platforms, supporting rapid incubation of new products and empowering enterprise clients (ToB).
Responsibilities
1. Design intelligent development toolkits for large-scale recommendation systems, providing tooling and productized solutions to enhance R&D efficiency.
2. Develop business metrics-driven gray release systems to ensure safe, stable, and efficient release strategies and workflows.
3. Enhance observability of recommendation systems in complex global environments (multi-region, multi-data center, multi-language), establish end-to-end tracing systems, and optimize issue attribution mechanisms.
4. Build algorithm engineering toolchains to accelerate the end-to-end process from experimental algorithm/model development to deployment, improving iteration efficiency.
5. Overhaul platform ecosystem architectures and develop data intelligence assistants.
Report job
