Multimedia AI LLM Post-Training Intern

Job Description

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

The Tone:
This is a temporary internship at TikTok, which is focused on building, researching, and applying Large Language Models (LLMs) to power its global products. The Multimedia AI team believes the most impactful problems in AI arise at the intersection of research and real-world deployment, and this role specifically addresses that intersection within the critical post-training phase of LLM development. Internships at TikTok aim to provide hands-on experience in developing fundamental skills and exploring potential career paths, fostering personal and professional growth through real-world scenarios.

The TL;DR
• Role: Internship
• Type: Temporary
• Location: In-person, Los Angeles, CA (potential)
• Pay: $45 hourly
• Team: Multimedia AI team
• Mission: Develop and optimize post-training strategies for Large Language Models to improve model performance, helpfulness, and safety across diverse multimedia product use cases.
• Tech Stack: Python, PyTorch, JAX, DeepSpeed, Megatron-LM

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

The Must-Haves
• Background: Currently pursuing an Undergraduate or Master’s degree in Computer Science, Machine Learning, or a related technical discipline. Must be able to commit to working for 12 weeks in 2026.
• Experience: No specific years of experience required; a foundational understanding of Transformer architectures and LLM training principles is essential.
• Skills: Strong programming skills in Python and experience with deep learning frameworks such as PyTorch or JAX. Demonstrated ability to learn quickly and a strong passion for AI application and product landing.
• Bonus: 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 through internships, open-source contributions, or academic research.