Machine Learning Engineer, Monetization Data Alignment

Role Summary

We are looking for an experienced Machine Learning Engineer to join the Monetization Data Alignment team. This role sits at the intersection of AI labeling, content understanding, multimodal large models, and agentic systems. You will work on building the next generation of scalable intelligence capabilities that power TikTok monetization use cases, with a strong focus on high-quality data, multimodal reasoning, and production-grade ML systems.

In this role, you will contribute to both research and production: from exploring LLM/MLLM, Agent, and reinforcement learning techniques, to delivering robust systems for labeling automation, multimodal understanding, rule retrieval, agent development, and interpretable decision-making.

Responsibilities

As TikTok's monetization ecosystem continues to grow across ads, e-commerce, short video, and live streaming, the demand for accurate, scalable, and efficient labeled data and content understanding systems is increasing rapidly. Our team is responsible for improving how commercial content is understood, labeled, structured, and operationalized at scale. We combine advanced machine learning with strong engineering execution to support data production, model innovation, and business impact.

• Design and develop machine learning solutions for AI labeling and content understanding in TikTok monetization scenarios, supporting ads, short video, and other monetization products.
• Apply and improve LLM/MLLM, NLP, CV, and multimodal learning techniques to enhance fine-grained understanding across text, image, audio, video, and live content.
• Build algorithms and systems for labeling automation, intent recognition, taxonomy/tag generation, rule retrieval, risk detection, and quality evaluation, improving both model accuracy and operational efficiency.
• Explore and productionize Agent and RL based approaches for complex decision-making workflows, including multi-step reasoning, tool use, and adaptive content analysis.
• Develop interpretable solutions such as CoT-style reasoning, explanation generation, and traceable decision logic to improve trustworthiness and operational usability of model outputs.

Requirements

Minimum Qualification(s)

• Bachelor's degree or above in Computer Science, Artificial Intelligence, Mathematics, Statistics, or related fields.
• 3+ years of experience in machine learning, applied AI, or related algorithm engineering roles, with hands-on experience in taking models or AI systems from experimentation to production.
• Solid foundation in machine learning and deep learning, with strong understanding of one or more of the following areas: LLM/MLLM, NLP, CV, multimodal learning, representation learning, or intelligent agents.
• Hands-on experience with large model training, fine-tuning, evaluation, inference, or deployment; familiarity with techniques such as prompting, supervised fine-tuning, retrieval augmented generation, chain-of-thought style reasoning, model alignment, or agent workflows.
• Ability to break down ambiguous business problems, design practical ML solutions, and collaborate effectively with cross-functional stakeholders in a fast-paced environment.
• Strong communication skills in English, and the ability to work effectively with global teams across research, product, engineering, and operations.

Preferred Qualification(s)

• Experience in AI labeling, content understanding, ads understanding, multimodal tagging, taxonomy systems, or data quality systems is highly preferred.
• Familiarity with Agent, reinforcement learning, RLHF/RLAIF, autonomous decision systems, or multi-step reasoning pipelines.
• Track record of strong research or innovation output, such as publications, patents, open-source contributions, or high-impact internal technical projects.
• Publications in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP, KDD, WWW, AAAI, IJCAI, or related areas are a strong plus.

About the Company

The Global Business Solutions (GBS) team is responsible for the revenue growth of the TikTok business, and our teams include Sales, Marketing, Ops, Account Managers, Agency and partnerships, as well as Marketing Science.

At TikTok, our Global Business Solutions (GBS) team plays a key role in generating revenue by promoting our advertising solutions, onboarding new clients, driving ad campaigns, and more. As the TikTok community grows at an unprecedented speed around the world, our GBS team leads groundbreaking projects that are changing the landscape of the advertising industry in real time.

We're seeking an analytically driven, and detail-oriented Client Solutions Manager (CSM) Intern to join our Ecommerce Team. As a CSM, you will partner closely with Client Partners and Client Solutions Managers to drive revenue by identifying opportunities, leveraging data insights, and delivering consultative solutions for advertisers.

This role centers on client education, relationship growth, data analysis, and campaign success. You will provide strategic recommendations to both clients and internal teams, ensuring campaigns achieve business objectives while optimizing long-term partnerships. Success in this role requires strong data analytics skills, adaptability in a fast-paced environment, and a test-and-learn mindset to uncover the best solutions.