AI Product Operations Intern(-Platform Responsibility-Teen Experiences)- 2027 Summer San

Location:

San Jose

Intern

A135308A

About the Team

We are building the next generation of content safety and governance systems at Tik Tok, with a strong focus on protecting minors and teens at global scale. Our team sits at the intersection of product, policy, and AI, leveraging large language models and multimodal technologies to design safety mechanisms that are proactive, scalable, and measurable. We work closely with Policy, Legal, Algorithm, and Engineering teams to translate complex regulatory and safety requirements into real-world product solutions that protect users while preserving a high-quality user experience.

We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.

Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted. Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.

• Support model strategy and operations for Tik Tok Minor Safety, working closely with cross-functional teams to participate in the end-to-end process of model design, optimization, training, and evaluation. Identify performance gaps and vulnerabilities in models, and propose effective actions to continuously improve model quality.
• Participate in the full data production lifecycle, including defining dataset standards, executing model evaluations, and ensuring high-quality data delivery.
• Explore and adopt the latest Large Language Model (LLM) tools to continuously optimize data production workflows and processes, improving efficiency and scalability. Stay up to date with industry trends to help build more intelligent and efficient data systems.
• Research emerging model training methodologies from both academia and industry, identify weaknesses in existing training data, and propose innovative solutions to improve data generalization, production efficiency, and coverage.

Minimum Qualifications
- Currently pursuing an Undergraduate/Master degree in computer science, data science, product management, or other related discipline. Basic understanding or strong interest in large language models (LLMs); willingness to learn related knowledge and tools (e.g., basic API usage). Good learning ability, logical thinking, and analytical skills; able to identify simple problems in daily work and try to propose solutions with guidance.

Preferred Qualifications
- Experience in Trust & Safety, content moderation, or familiarity with content safety compliance requirements is a strong plus. Hands-on experience in data analysis or model optimization is preferred.

The hourly rate range for this position in the selected city is $25- $25.

• Interns have day one access to health insurance, life insurance, wellbeing benefits and more.
• Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year).
• Interns who are not working 100% remote may also be eligible for housing allowance.

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of…