Senior Software Engineer, Recommendation Engine System
TikTok
San Jose, CA · Posted November 13, 2026
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How AI is used in this kind of work
Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
TikTok has filed one layoff notice in the last twelve months, covering 250 workers, most recently August 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings
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About the job
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.
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.