Job Description
Our Company will be prioritizing applicants who have a current right to work in Singapore, and do not require Our Company's sponsorship of a visa.
About the Team
The AI Data Service and Operations (ADSO) team is responsible for providing safety and non-safety data annotation services and search operation services for all of the company's international products, which can also help international products build their own data ecological security.
The Safety Model Operations [SMO] team within ADSO is responsible for building, optimizing, and maintaining machine learning models and operational processes that support TikTok's Trust & Safety systems. We ensure that automated safety models perform effectively in identifying harmful content, mitigating risks, and maintaining a safe user environment across regions.
What will I do?
1. Responsible for end-to-end project delivery management for content safety model training and evaluation data — from requirements analysis and solution design to execution and continuous optimization — ensuring projects are completed efficiently and with high quality.
2. Deeply understand business goals and data requirements from algorithm, product, and other teams. Lead the development and iteration of data production strategies, transforming complex business problems into actionable, scalable data solutions.
3. Establish and continuously optimize standardized processes, operational guidelines, and quality systems for data production. Identify efficiency bottlenecks and quality risks, and improve delivery efficiency and stability through mechanism design, tooling, and automation.
4. Act as the core driver of projects, coordinating with algorithm, product, annotation, operations, and other cross-functional teams. Manage project timelines, identify and resolve blockers and risks to ensure objectives are met.
5. Build quality assessment and retrospective mechanisms for project delivery. Use data monitoring, root cause analysis, and case studies to drive continuous improvement in delivery quality and team effectiveness, while establishing reusable best practices.
