Responsibilities

Team Overview We are an AI-First LLM Strategy Operations team responsible for scaling large language model (LLM) capabilities across e-commerce service scenarios. Our mission is not only to apply LLMs to service workflows, but to build a sustainable operational system that enables LLM capabilities to continuously improve service efficiency and user experience. The team focuses on the full lifecycle of LLM applications, including infrastructure, evaluation systems, data assets, and operational workflows. Through systematic experimentation and operational mechanisms, we aim to transform LLM adoption from isolated pilots into scalable, measurable, and continuously evolving solutions. 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. Key Responsibilities: Depending on your interests and background, you may support one or more of the following areas: 1. AI Solution Exploration Assist in exploring how LLM capabilities can be applied to real e-commerce service scenarios such as after-sales, logistics, and customer inquiries. Support the team in: - Conducting LLM solution research and benchmarking - Building prototype workflows, demos, or PoCs - Analyzing real service cases and identifying opportunities for AI optimization - Supporting prompt design, knowledge retrieval testing, and workflow experiments Through these activities, you will gain exposure to how AI solutions are translated into real business impact. 2. LLM Operations Infrastructure Assist in building operational infrastructure that supports large-scale LLM applications, including: - Organizing and structuring service knowledge bases - Supporting evaluation dataset preparation and testing workflows - Assisting with model testing, benchmarking, and experiment documentation - Supporting the design of operational processes such as testing pipelines and deployment tracking This work will help you understand how LLM systems are operationalized and governed in large organizations. 3. Data Governance & Annotation Support - Support the preparation and management of data used for model training and evaluation. Responsibilities may include: - Assisting in annotation guideline design and data labeling - Conducting data quality checks and sampling audits - Organizing datasets for model evaluation and case libraries - Supporting experiments that explore human-AI collaboration in data production Through this work, you will gain experience in building high-quality AI datasets and evaluation frameworks.

Qualifications

Minimum Qualification(s): - Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Information Systems, business or related fields - Strong analytical and structured thinking ability - Interest in LLMs, AI applications, or intelligent systems - Good communication skills and ability to collaborate in cross-functional teams Preferred Qualification(s): - Basic familiarity with LLM concepts, prompt engineering, or AI agents - Experience with Python, data analysis, or AI experimentation tools - Experience with LLM tools, APIs, or AI platforms If you have any questions, please reach out to us at apac-earlycareers@tiktok.com

Job Information