Machine Learning Project Intern (Business Integrity Data Cycling Center) - 2026 Start (BS/MS)

Team Introduction:

TikTok’s Generative AI and Monetization ecosystem relies on large-scale, high-quality data to sustain model performance, safety, and product innovation as the business continues to scale. Ensuring data quality, coverage, and efficiency is a foundational requirement for long-term Generative AI advancement.

The Data Solutions Team owns the data layer that powers Monetization-related Generative AI systems. The team combines deep understanding of Generative AI model behavior, evaluation dynamics, and failure patterns with quantitative and qualitative analysis to drive systematic improvements in data quality and model outcomes.

Operating on a global scale, the team focuses on high-value dataset curation, data infrastructure and processing capabilities, and data-driven discovery of opportunities that unlock next-generation Generative AI capabilities. By transforming insights from model evaluation, human feedback, and data analysis into scalable data assets, the team enables sustainable model improvement and product growth.

We are looking for passionate Machine Learning Engineer Interns that have strong problem solving skills to join forces with talented cross functional partners (business operation, data science, engineering and product management) to tackle cutting-edge challenges in the realm of generative AI. In this role, you will contribute to the company's core business across innovative advertising products, campaign management and measurement solutions. You will see a direct impact from your day-to-day work to customer satisfaction and company growth.

As a project intern, you will have the opportunity to engage in impactful short-term projects that provide you with a glimpse of professional real-world experience. You will gain practical skills through on-the-job learning in a fast-paced work environment and develop a deeper understanding of your career interests.

Applications will be reviewed on a rolling basis - we encourage you to apply early. Successful candidates must be able to commit to at least 3 months long internship period.

Responsibilities:

• Support dataset construction and data quality initiatives, including sampling, preprocessing, label validation, and root cause analysis of human annotation inconsistencies.
• Build and improve model evaluation frameworks for state-of-the-art generative AI models in production, and/or contribute to the iteration of next-gen generative AI models
• Contribute to human-in-the-loop systems by analyzing human annotator behavior, and ML-assisted labeling strategies to improve efficiency and reliability.
• Work closely with Product Managers, Data Scientists/Analysts, and cross-functional Software/Machine Learning Engineers to understand AIGC evaluation, safety, and data requirements, translating business problems into measurable ML tasks.
• Communicate findings, experimental results, and data insights clearly to technical and non-technical stakeholders, supporting data-driven decision making.

Minimum Qualifications:

• Undergraduate or postgraduate candidate currently pursuing a degree in Machine Learning, Computer Science, Software Engineering, or a closely related quantitative