Software Engineer Intern (TikTok Eng - AI Platform) - 2025 Project Intern (BS/MS)

TikTok to build the infrastructure that powers agile model iteration and brings AI into every corner of the business.

Internships at TikTok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth.

Applications will be reviewed on a rolling basis - we encourage you to apply early.
Successful candidates must be able to commit to at least 12-week long internship period.

As a member of TikTok PGG AI Platform team, you will:

• Responsible for developing our AI Platform by using cutting-edge AI technologies such as LLM, MLLM, RAG, and Agents.
• Work closely with product managers, algorithm teams, and other cross-functional stakeholders to tackle complex, high-impact problems.
• Design and evolve system architecture to ensure scalability, performance, and reliability. Build robust infrastructure to integrate LLM capabilities into real-world business applications.
• Learn how TikTok core products work, and discover the magic underlying systems that power the fastest-growing platform on the planet.

Qualifications

Minimum Qualifications:

• Currently pursuing Bachelor's or Master's in Computer Science or related field.
• Proficiency in at least one of the following programming languages: Golang, Python, or JavaScript, along with familiarity with common development frameworks and tools.
• Curiosity towards new technology and outstanding ability to analyze and solve problems.
• Practical experience working with genAI/LLM systems, AI agents, and related data processing workflows

Preferred Qualifications:

• Active participation in open-source projects and strong familiarity with the AI/ML community.
• Solid understanding of machine learning fundamentals, deep learning frameworks (e.g., PyTorch, TensorFlow), and widely used AI development tools.
• Deep passion for AI - you think about it, read about it, and build with it every day.