Content Quality and Evaluation Specialist (Mandarin Speaking) - Safety Model Operations

Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia Until 8/22/2026 H-1B sponsor history First posted April 28, 2026 Last posted April 28, 2026
Job description

Description

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

Responsibilities
1. Construct and iterate the core Golden Sets for the content safety ecosystem. Curate long-tail, high-risk, and complex edge cases to establish highly accurate data standards (Ground Truth) for platform safety policies, AI model evaluation, and global enforcement teams.
2. Conduct deep-dive analyses on high-risk and highly debated safety cases to accurately identify misapplication patterns and risk evolution trends. Lead the synthesis and abstraction of complex rules, translating macro policies into highly logical and executable Standard Operating Procedures (SOPs) and operational guidelines.
3. Drive the content safety data closed-loop. Collaborate cross-functionally with Operations, Algorithm, Product, and global teams to identify system vulnerabilities based on Golden Set metrics, achieving bidirectional improvements in human review quality and AI agent interception efficacy.
4. Systematize universal methodologies for the content quality management framework and establish robust daily Quality Assurance (QA) mechanisms. Track and attribute core data metrics to enhance overall data accuracy and operational efficiency.

Requirements

Minimum Qualification(s)
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. Mandarin proficiency is also required, as it is mandatory for daily liaison with the China team in the China market and the accurate communication of business information.

Preferred Qualification(s)
1. Familiarity with machine learning logic and data labeling frameworks is a strong plus.

About this role

Summary

Perform quality assurance and analysis for AI safety models in a fast-paced environment.

Job title

Content Quality and Evaluation Specialist (Mandarin Speaking) - Safety Model Operations

Experience level

null

Industry

software

Location requirements

Kuala Lumpur, Malaysia; remote not specified.

Salary

Not specified

Visa sponsorship

H-1B sponsor history

Management role

No

Skills & keywords

Required skills

englishmandarinquality assurancedata evaluation

Preferred skills

machine learningdata labeling

Specializations

quality assuranceai data evaluationcontent safetymachine learning
Locations

Structured locations inferred from the posting.

Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Work arrangement unknown City