Search Safety Operations Intern（TikTok-Platform Responsibility-Search）- 2027 Summer

TikTok; San Jose (CA); On-site; USD 34,000 - 48,000; Full time

Job summary

TikTok is seeking a Search Safety PM Intern to help train and improve next-generation large language models for its search safety workflows. You will build datasets, design prompts, and generate labeled data to power model learning and performance.

This internship focuses on content understanding, language, and applied AI, with opportunities to work closely with cross-functional teams and participate in hands-on training and workshops.

Qualifications

• Currently pursuing an Undergraduate/Master's in CS, data science, or related field.
• Strong content sensitivity and analytical thinking with attention to nuance.
• Excellent English writing and communication at scale.
• Interest in large language models and AI workflows.
• Ownership, execution, and ability to handle large volumes of work.

Responsibilities

• LLM Training Data & Knowledge Base Development: build high-quality datasets and knowledge bases for LLM training.
• Prompt Design & Model Interaction: draft prompts and optimize for training scenarios; analyze model outputs.
• Content Understanding & Quality Assurance: interpret complex content and ensure data quality and guidelines.
• Iteration & Improvement: refine data standards based on model feedback and project needs.

Skills

Attention to detail

Strong writing

Analytical thinking

English proficiency

Content understanding

Ownership & execution

Learning agility

Education

Undergraduate/Master's in CS/Statistics/Data Science or related

Tools

LLM platforms

Job description

About the Team
The Safety Product team is at the forefront of building and optimizing content safety systems. With a focus on optimising and advancing content safety, we leverage advanced large language models to enhance review efficiency, risk control, and user trust. Working closely with business and technical stakeholders, we deliver scalable solutions that keep pace with rapid global growth.

We are seeking a passionate and detail-oriented Search Safety PM Intern to join our team and play a pivotal role in safeguarding the health and security of our search business. Your core mission will be to support the development and training of next-generation large language models. In this role, you will work closely with the team to build high-quality training resources, design effective prompts, and generate large-scale labeled datasets that directly power model learning and performance.

This position sits at the intersection of content understanding, language, and applied AI. You will leverage strong analytical thinking and language skills to transform complex real-world content into structured, high-quality training data for LLMs. Your work will play a foundational role in shaping model behavior, alignment, and real-world usability.

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.

Responsibilities

LLM Training Data & Knowledge Base Development

• Training Corpus Construction: Assist in building and maintaining high-quality datasets and knowledge bases for new LLM training initiatives, ensuring accuracy, diversity, and contextual richness.
• Label System Design & Scaling: Help design labeling frameworks and taxonomies, and generate large-scale, high-consistency labeled datasets to support supervised and reinforcement learning workflows.
• Data Generation & Curation: Produce, review, and refine large volumes of training data based on defined standards, use cases, and evaluation criteria.

Prompt Design & Model Interaction

• Prompt Writing & Optimization: Draft, iterate, and optimize prompts for different training and evaluation scenarios, ensuring clarity, coverage, and alignment with model objectives.
• Model Behavior Analysis: Analyze model outputs to identify gaps, biases, or failure patterns, and translate insights into improved prompts or data requirements.
• LLM Familiarity & Application: Apply a strong understanding of LLM capabilities and limitations to design data and prompts that meaningfully improve model performance.

Content Understanding & Quality Assurance

• Content Interpretation: Deeply understand complex content across domains, identify key signals, intent, and nuances, and convert them into structured training inputs.
• Quality Control: Conduct quality reviews on datasets, labels, and prompts, ensuring consistency, logical soundness, and adherence to guidelines.
• Iteration & Improvement: Continuously refine data standards and workflows based on model feedback and project needs.

Minimum Qualifications

• Currently pursuing an Undergraduate/Master's in computer science, statistics, information management, data science or a related discipline.
• Strong Content Sensitivity & Analytical Thinking: Excellent ability to understand, interpret, and structure complex textual content, with high attention to detail and nuance.
• Outstanding English Proficiency: Exceptional English writing and communication skills, with the ability to produce clear, precise, and logically structured content at scale.
• LLM Awareness & Learning Agility: Strong interest in large language models, with the ability to quickly learn AI-related concepts, tools, and workflows and apply them in practice.
• Ownership & Execution Ability: Highly responsible, self-driven, and capable of handling large volumes of work with consistency and quality.

Preferred Qualifications

• Humanities / Social Sciences Background: Currently pursuing or recently completed a major in humanities, social sciences, foreign languages, international relations, or related fields.
• Prior experience in content annotation, data labeling, research assistance, or AI-related operations.
• Experience interacting with LLMs (e.g., prompt engineering, evaluation, or content generation projects).