LLM Post-training Engineer Intern (Research & Product) - 2026 Summer (BS/MS)

The Multimedia AI team at TikTok focuses on building, researching, and applying Large Language Models (LLMs) to power our global products. We believe the most impactful problems in AI arise at the intersection of research and real-world deployment—and post-training is where that intersection is sharpest.

We are looking for talented individuals to join us for an internship in 2026. Internships at our Company aim to offer students industry exposure and hands-on experience. Watch your ambitions become reality as your inspiration brings infinite opportunities at our Company.

Internships at Our Company aims 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.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to Our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).

Summer Start Dates: May 11th, 2026 May 18th, 2026 May 26th, 2026 June 8th, 2026 June 22nd, 2026

Responsibilities

• Support the development and optimization of post-training strategies, including instruction tuning, preference tuning (SFT/DPO/PPO), and model alignment. - Assist in building robust evaluation pipelines to measure model performance, helpfulness, and safety across diverse multimedia product use cases. - Participate in the research and implementation of cutting-edge methodologies in reward modeling and human preference learning. - Collaborate with engineering teams to bridge the gap between experimental research and production-ready AI applications (e.g., video understanding, translation, and content classification). - Analyze and process large-scale datasets to identify patterns that improve model behavior and alignment quality.