Machine Learning Engineer - Monetization Data Alignment

Role Overview

Join TikTok's Monetization Data Alignment team as a Machine Learning Engineer, focusing on the scalable intelligence systems that support the platform's rapidly expanding monetization ecosystem, including ads, e-commerce, short video, and live streaming. This position bridges AI labeling, content understanding, multimodal large models, and agentic systems to build high-quality data solutions and production-ready ML implementations.

Responsibilities

• Develop machine learning methods tailored for AI-driven labeling and content comprehension within TikTok's monetization products such as ads and short videos.
• Leverage and enhance large language and multimodal models (LLM/MLLM), natural language processing, computer vision, and multimodal learning techniques to achieve nuanced interpretation of diverse content formats including text, images, audio, video, and live streams.
• Create algorithms and systems to automate labeling, recognize user intent, generate taxonomies and tags, retrieve rules, detect risks, and evaluate data quality, thereby boosting model precision and operational productivity.
• Innovate and operationalize agent-based and reinforcement learning strategies for intricate decision-making workflows involving multi-step reasoning, tool utilization, and adaptive content review.
• Design interpretable ML models implementing chain-of-thought reasoning, explanation generation, and traceable decision-making to enhance trust and usability in production systems.

Qualifications

• Bachelor's degree or higher in Computer Science, AI, Mathematics, Statistics, or related disciplines.
• Minimum of 3 years of professional experience applying machine learning or artificial intelligence techniques, with proven capability of transitioning models from experimental phases to robust production deployment.
• Strong foundational knowledge in machine learning and deep learning, especially in areas such as large and multimodal language models, computer vision, representation learning, natural language processing, or intelligent agent design.
• Practical experience in training, fine-tuning, evaluating, inferring, and deploying large-scale models, including familiarity with advanced methods like supervised fine-tuning, prompt engineering, retrieval-augmented generation, and chain-of-thought reasoning.
• Capability to dissect complex and ambiguous business challenges, architect feasible ML solutions, and collaborate efficiently with diverse teams in a dynamic environment.
• Excellent English communication skills, capable of coordinating with global research, product, engineering, and operations teams.
• Preferred: Experience related to AI labeling, content understanding for ads, multimodal tagging, taxonomy frameworks, or data quality initiatives.
• Exposure to agent frameworks, reinforcement learning, RLHF/RLAIF methodologies, autonomous decision systems, or pipelines requiring multi-step reasoning is advantageous.
• Demonstrated research contributions through publications, patents, open-source projects, or impactful internal technical achievements are highly valued.

About TikTok

TikTok is a premier platform for short-form mobile videos, aiming to spark creativity and bring joy globally. Headquartered in Los Angeles and Singapore, TikTok operates extensive offices worldwide.

Culture and Values

The company emphasizes a culture of curiosity, humility, and impact with a dynamic, rapidly growing environment that turns challenges into learning and innovation opportunities. TikTok values diversity and inclusivity, striving for a workplace that reflects the broad communities it serves, fostering an environment where all employees’ voices and skills are appreciated.