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:

• Design, develop, and optimize large-scale recommendation engine systems to enhance content discovery.
• Build and maintain high-performance, low-latency, and scalable infrastructure using C++ and modern system development frameworks.
• Implement multi-threaded and concurrent computing techniques to support real-time recommendations.
• Develop and optimize distributed systems for large-scale data processing and model inference.
• Continuously improve performance and efficiency through profiling, benchmarking, and optimization.

Qualifications

Minimum Qualifications:
- Bachelor's degree or above, majoring in Computer Science or related fields, with experience building scalable system.
- Experiences with C++ in large-scale system development.
- Strong understanding of concurrent programming, multi-threading, and distributed systems.
- Experience with high-performance computing and large-scale data processing frameworks.
- Familiarity with system architecture, caching strategies, and performance optimization.

Preferred Qualifications:

• Experience in recommendation systems, search ranking, or personalization engines.
• Proficiency in big data processing frameworks (e.g., Flink, Spark, Hadoop) and real-time data pipelines.
• Experience with high-throughput, low-latency system design.
• Knowledge of GPU acceleration for ML inference is a plus.