About the job
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.
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.
Qualifications
Minimum
Currently pursuing an Undergraduate or Master’s degree in Computer Science, Machine Learning, or a related technical discipline.
Strong programming skills in Python and experience with deep learning frameworks such as PyTorch or JAX.
Foundational understanding of Transformer architectures and LLM training principles.
Demonstrated ability to learn quickly in a fast-paced environment and a strong passion for AI "landing" and product application.
Able to commit to working for 12 weeks in 2026
Preferred
Previous experience or research projects involving LLM fine-tuning, RLHF, or synthetic data generation.
Familiarity with distributed training tools (e.g., DeepSpeed, Megatron-LM).
Experience or interest in multimodal AI (integrating text with video or audio).
Proven track record of building and deploying AI projects, either through previous internships, open-source contributions, or academic research.