Contribute to research and optimization of TikTok’s planet-scale business architecture, supporting billions of users, globally distributed ultra-large-scale data centers, and microservice clusters with millions of services. - Assist in data modeling and algorithmic optimization to address key challenges in large-scale infrastructure and business architecture, including but not limited to capacity forecasting and planning, service and data placement optimization, traffic scheduling optimization, and risk prediction. - Under the guidance of mentors, transform research insights into prototypes, tools, or frameworks, and explore their applicability in selected business scenarios. - Participate in analyzing research data, summarizing experimental results, and contributing to academic publications in top-tier conferences/journals. - Collaborate with architecture, platform, and business teams to understand real-world production challenges and explore potential optimization opportunities. Requirements: Minimum Qualifications: - Currently pursuing a PhD in Computer Science, Software Engineering, Systems Engineering, Operations Research, Applied Mathematics, or related fields. - Solid research background in distributed systems, large-scale system optimization, or AI for Systems. - Able to commit to working for 12 weeks during Summer 2026 - Strong problem-solving skills with the ability to model planet-scale, complex business and infrastructure systems, abstract key variables and constraints, and clearly articulate solutions through rigorous logical reasoning and effective communication. - Familiarity with optimization algorithms such as integer programming, dynamic programming, graph optimization, heuristic search, or reinforcement learning, with the ability to apply them to large-scale optimization problems. - Proficiency in at least one mainstream programming language (e.g., Go, Java, C , Python), with the capability to build research prototypes. - Ability to quickly learn and deeply understand complex architectural patterns, while leveraging AI tools and automation methods to improve research and development efficiency. Preferred Qualifications: - Experience in data modeling and analysis for large-scale systems or business architectures. - Research publications or submissions to top-tier conferences/journals such as OSDI, SOSP, NSDI, So. CC, SIGCOMM, KDD, Neur. IPS. - Hands-on project experience in distributed systems, resource scheduling, or architecture optimization (including academic projects or previous internships). - Familiarity with performance and optimization challenges in cross-data-center or cross-region architectures. By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: