Monetization ML Engineer: Data Alignment & LLMs

TikTok; Singapore; On-site; SGD 140,000 - 230,000; 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 large models, and agentic systems to power TikTok monetization use cases.

You will contribute to both research and production, exploring LLM/MLLM, Agent, and RL techniques, and delivering robust systems for labeling automation, multimodal understanding, and interpretable decision-making.

Qualifications

• Bachelor’s degree or above in CS, AI, Math, or related fields.
• 3+ years in ML or AI with production experience.
• Strong understanding of LLM/MLLM, NLP, CV, multimodal learning.
• Hands-on experience with large model training, fine-tuning, evaluation, inference.
• Ability to translate business problems into ML solutions and collaborate with teams.
• Excellent English communication across 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 for fine-grained understanding.
• Build algorithms for labeling automation, intent recognition, taxonomy generation, rule retrieval, risk detection, and quality evaluation.
• Explore and productionize Agent and RL approaches for complex decision-making workflows.
• Develop interpretable solutions such as CoT reasoning, explanations, and traceable decision logic.

Skills

ML engineering

LLM/MLLM expertise

Multimodal learning

Production ML systems

English communication

Education

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

Tools

Large model training

Fine-tuning

Retrieval augmented generation

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 large models, and agentic systems to power TikTok monetization use cases.

You will contribute to both research and production, exploring LLM/MLLM, Agent, and RL techniques, and delivering robust systems for labeling automation, multimodal understanding, and interpretable decision-making.