Software Engineer, Ads Measurement Signal and Privacy - Infra

Our Ads Measurement Signal and Privacy team (MSP) is missioned to build our security and governance infrastructure and process for the ads system end-to-end while making sure our platform with large volume of various signals and data are constantly compliant with regional regulations across the world. The team will be responsible for exploring and implementing cutting-edge privacy-enhancing technologies to protect our users while keeping TikTok a free and creative community. You will be a key player in data privacy, protection, security and managing cross-functional programs to continuously improve the process.

Responsibility 1. Responsible for building a graph-based system architecture in advertising business scenarios, establishing innovative R&D, delivery, and O&M models to achieve intelligent resource orchestration. 2. Participate in developing new capabilities such as graph execution engines, hot updates for operators, and graph-based delivery systems, while driving business abstraction and refactoring of critical modules in advertising systems. 3. Break down long-term goals into actionable implementation paths, organize and lead project teams to build a graph-based Serverless infrastructure foundation. 4. Implement operator-driven computational orchestration for advertising systems using engineering models, continuously optimize system throughput and latency to deliver tangible business benefits.

Minimum Qualifications: • BS/MS Degree in Computer Science, Computer Engineering or relevant technical field, with related working experience. • Experienced in building backend services for large-scale consumer-facing applications. • Proficiency in at least one of the following languages: Go, C++, Java, Go, Python. • Good communication and teamwork skills.

Preferred Qualifications: • Experience collaborating with compliance and policy teams, government entities, external privacy-focused community members and members of the press. • Experience with cutting-edge data privacy security technologies, such as differential privacy, homomorphic encryption, federated learning etc. Specific production practices are preferred. • Experience in Ads domain.