Content Quality and Evaluation Specialist - Japanese

About the team The Safety Model Operations [SMO] team 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.

The SMO Delivery Team plays a critical role in the organization. Its primary responsibility is to carry out the full spectrum of quality assurance activities for each project. This includes:

• Conducting detailed reviews and complex RCA's to ensure labeling accuracy and consistency
• Monitoring quality performance and compliance against project-specific KPIs
• Identifying trends, risks, and potential gaps in processes or guidelines
• Providing structured feedback and improvement recommendations to the Central Project Team
• Supporting continual optimization of workflows, tools, and evaluation methodologies
• Improve Model performance of AI models

Requirements

Minimum Qualifications:

1. Proven experience in internet Trust & Safety, Quality Assurance (QA), AI data evaluation, or policy operations.
2. Exceptional logical reasoning and synthesis skills. Proven ability to navigate complex and ambiguous business scenarios to identify underlying root causes and independently deliver structured solutions.
3. Professional working proficiency in English. Extreme attention to detail and standard consistency, paired with outstanding cross-cultural written and verbal communication skills.
4. Highly self-motivated with a strong sense of ownership. Capable of embracing uncertainty in a fast-paced, cross-border collaborative environment, effectively driving multiple parallel tasks to deliver solid business results.
5. Japanese proficiency is also required, as it is mandatory for daily liaison with the local team in the Japan market and the accurate communication of business information.

Preferred Qualifications:

1. Familiarity with machine learning logic and data labeling frameworks is a strong plus.