About the job
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.
Responsibilities
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.
Qualifications
Minimum
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field.
Experience in building large-scale recommendation, ranking, or search systems.
Experience in C++, Go, or Python, and with distributed computing frameworks.
Solid understanding of ranking algorithms, machine learning inference systems, and system performance optimization.
Preferred
Experience in machine learning platform infrastructure, particularly online prediction serving or ranking pipelines.
Familiarity with feature engineering pipelines, model lifecycle management, and A/B testing systems.
Experience working with multi-threading, memory management, and low-latency service architectures.
Proven ability to lead complex projects across multiple teams and stakeholders.