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 (ML) 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 You Will Do

- Own and optimize the end-to-end Machine Learning Operations (MLOps) lifecycle for safety models, including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.

- Design, implement, and continuously improve automated ML pipelines (training, inference, and evaluation) to increase efficiency, scalability, and reliability.

- Collaborate with ML Engineers, Data Scientists, and other relevant cross functional teams to identify model performance gaps, data drift, and production issues, then drive initiatives to resolve them.

- Explore and integrate the latest MLOps tools, frameworks, and LLMOps best practices to streamline experimentation, model versioning, CI/CD for ML, and automated retraining.

- Establish and maintain robust model monitoring, observability, and alerting systems to detect performance degradation, bias, and data quality issues in production.

- Lead initiatives to improve training data quality and coverage by developing advanced data pipelines, synthetic data strategies, and active learning approaches.

- Take end-to-end ownership of model operations — from dataset curation and standard setting to production deployment and post-launch performance tracking.

- Stay current with cutting-edge research and industry trends in MLOps, LLMOps, and scalable model serving.