Key skills
Machine LearningML
About this role
About The Team
TikTok’s recommendation system is at the core of our user experience, delivering personalized content to millions of users in real time. Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for our recommendation system to provide the most stable and best experience for our TikTok users.
What you will be doing:
- Architect, build, and optimize large-scale ranking systems that serve billions of daily recommendations with low latency and high precision.
- Design flexible, efficient, and scalable ranking frameworks to support evolving machine learning models and features.
- Collaborate with ML engineers to integrate ranking models into production, ensuring seamless inference, freshness, and feedback loops.
- Analyze system bottlenecks and apply performance optimizations at the framework and infrastructure level (CPU/GPU, memory, storage, networking).
- Drive technical excellence and best practices in software design, code quality, and system reliability.
TikTok’s recommendation system is at the core of our user experience, delivering personalized content to millions of users in real time. Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for our recommendation system to provide the most stable and best experience for our TikTok users.
What you will be doing:
- Architect, build, and optimize large-scale ranking systems that serve billions of daily recommendations with low latency and high precision.
- Design flexible, efficient, and scalable ranking frameworks to support evolving machine learning models and features.
- Collaborate with ML engineers to integrate ranking models into production, ensuring seamless inference, freshness, and feedback loops.
- Analyze system bottlenecks and apply performance optimizations at the framework and infrastructure level (CPU/GPU, memory, storage, networking).
- Drive technical excellence and best practices in software design, code quality, and system reliability.