Monetization Data ML Engineer: Multimodal AI Labeling

TikTok; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

TikTok is seeking an experienced Machine Learning Engineer to join the Monetization Data Alignment team. You will work at the intersection of AI labeling, content understanding, multimodal models, and agentic systems to build scalable intelligence for monetization use cases.

You will contribute to both research and production, exploring LLMs, agent methods, and reinforcement learning, while delivering robust labeling automation, multimodal understanding, and interpretable decision logic in

Qualifications

• Bachelor’s degree or above in CS/AI/Math or related fields.
• 3+ years in ML, applied AI, or related algorithm engineering with production experience.
• Strong foundation in ML/deep learning; expertise in LLM/MLLM, NLP, CV, or multimodal learning.
• Hands-on experience with large model training, fine-tuning, evaluation, inference, or deployment.
• Ability to translate ambiguous business problems into practical ML solutions and collaborate with cross-functional teams.
• Strong English communication; able to work with global teams.

Responsibilities

• Design and develop ML solutions for AI labeling and content understanding in monetization scenarios.
• Apply and improve LLM/MLLM, NLP, CV, and multimodal learning techniques across text, image, audio, video, and live content.
• Build algorithms for labeling automation, intent recognition, taxonomy/tag generation, rule retrieval, risk detection, and quality evaluation.
• Explore and productionize Agent and RL-based approaches for multi-step decision workflows.
• Develop interpretable solutions such as CoT-style reasoning, explanations, and traceable decision logic.

Skills

Machine Learning

Deep Learning

NLP

Multimodal learning

Agent workflows

Prompting

Model deployment

English communication

Education

Bachelor’s degree or above in CS/AI/Math

Job description

TikTok is seeking an experienced Machine Learning Engineer to join the Monetization Data Alignment team. You will work at the intersection of AI labeling, content understanding, multimodal models, and agentic systems to build scalable intelligence for monetization use cases.

You will contribute to both research and production, exploring LLMs, agent methods, and reinforcement learning, while delivering robust labeling automation, multimodal understanding, and interpretable decision logic in