1 day ago

Group Leader, Safety Model Operations (APAC) - AI Data Service Operations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Lead and scale operational teams in Safety Model Operations across APAC, driving high-quality AI moderation and labeling services. Own operational excellence and quality assurance by running RCAs, audits, and KPI monitoring, then translating findings into improved model outcomes. Coach team leads, manage data collection and reporting, and collaborate with product, engineering, policy, and data science teams to optimize annotation workflows, tools, and feedback loops (RLHF/RLAIF).

Location: Kuala Lumpur

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Lead, motivate, and develop large operational teams to deliver AI moderation and labeling services with clear accountability for operational KPIs and downstream model impact.
•Drive a deep understanding of how annotation quality, guideline design, and rater performance affect model training, safety, and alignment (including RLHF/RLAIF feedback loops).
•Conduct detailed reviews, complex root cause analyses (RCAs), and quality audits; link findings to model-level outcomes such as safety benchmark improvements and reduced hallucinations.
•Monitor quality performance and compliance against project KPIs, proactively identifying trends, risks, and gaps in processes, guidelines, or rater pools.
•Collaborate cross-functionally with product, engineering, policy, and data science to run experiments, measure impacts on model metrics, improve tools/workflows, and manage training programs and operational reporting.

Key Requirements

•Bachelor’s degree in business, management, operations, data science, or related field.
•Minimum 3 years of leadership experience managing managers, scaling high-performing teams in Trust & Safety, AI Operations, Data Annotation, or Tech Operations.
•Strong understanding of how human content moderation, data labeling, and QA processes impact AI model training, performance, safety, and alignment.
•Demonstrated experience in strategy development, operational execution, and data-driven decision making under tight timelines.
•Proficiency with data tools for operational analysis, including SQL and data visualization platforms (e.g., Power BI), to monitor quality metrics and trends.

Experience:3+ yearsAI moderationData labelingTrust & SafetyTech operations

Education:Bachelor's

Skills:LeadershipCommunicationStakeholder managementAnalytical problem-solvingSystems thinking

Tech Stack:SQLPower BI

Company Brief

TikTok

Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn

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TikTok

1 day ago

Group Leader, Safety Model Operations (APAC) - AI Data Service Operations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: Kuala Lumpur

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Lead, motivate, and develop large operational teams to deliver AI moderation and labeling services with clear accountability for operational KPIs and downstream model impact.
•Drive a deep understanding of how annotation quality, guideline design, and rater performance affect model training, safety, and alignment (including RLHF/RLAIF feedback loops).
•Conduct detailed reviews, complex root cause analyses (RCAs), and quality audits; link findings to model-level outcomes such as safety benchmark improvements and reduced hallucinations.
•Monitor quality performance and compliance against project KPIs, proactively identifying trends, risks, and gaps in processes, guidelines, or rater pools.
•Collaborate cross-functionally with product, engineering, policy, and data science to run experiments, measure impacts on model metrics, improve tools/workflows, and manage training programs and operational reporting.

Key Requirements

•Bachelor’s degree in business, management, operations, data science, or related field.
•Minimum 3 years of leadership experience managing managers, scaling high-performing teams in Trust & Safety, AI Operations, Data Annotation, or Tech Operations.
•Strong understanding of how human content moderation, data labeling, and QA processes impact AI model training, performance, safety, and alignment.
•Demonstrated experience in strategy development, operational execution, and data-driven decision making under tight timelines.
•Proficiency with data tools for operational analysis, including SQL and data visualization platforms (e.g., Power BI), to monitor quality metrics and trends.

Experience:3+ yearsAI moderationData labelingTrust & SafetyTech operations

Education:Bachelor's

Skills:LeadershipCommunicationStakeholder managementAnalytical problem-solvingSystems thinking

Tech Stack:SQLPower BI

Company Brief

TikTok

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn