AI Engineer PhD Intern – Multimodal AI

Job Description

Machine Learning Scientist Intern (TikTok-Content Ecology—LLM application) – 2026 Start (PhD) | TikTok

The Tone:
This is an internship at TikTok, with potential for in-person work in a selected city like Los Angeles, or remote. TikTok is the leading destination for short-form mobile video, focused on inspiring creativity and bringing joy to millions of daily users. This role matters as interns actively contribute to the company’s products and research, shaping future plans and emerging technologies that directly impact TikTok’s growth and user engagement.

The TL;DR
• Role: Internship
• Location: Flexible (Remote/In-person, e.g., Los Angeles)
• Pay: $60 hourly
• Team: Content Ecology Algorithm Team
• Mission: Improve TikTok’s content ecosystem and user engagement through advanced AI, including LLMs, NLP, CV, and recommendation algorithms.
• Tech Stack: TensorFlow, PyTorch, Python, C++

What You’ll Actually Do
• Model Development: Develop and optimize LLM, NLP, CV, and recommendation models to improve TikTok’s content ecosystem.
• Multimodal AI: Implement multimodal AI solutions, integrating video, text, and speech understanding.
• System Optimization: Optimize LLM-powered search, discovery, and content recommendation systems for better user engagement.
• Deep Learning: Train and fine-tune deep learning models using TensorFlow, PyTorch, or other ML frameworks.
• Deployment & Collaboration: Deploy and scale machine learning solutions in a distributed computing environment and work closely with AI researchers, software engineers, and business teams.

The Must-Haves
• Background: Doctorate Degree. Student pursuing a PhD in Computer Science, Machine Learning, AI, or a related field.
• Experience: Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch, and a solid understanding of machine learning, NLP, CV, or recommendation algorithms.
• Skills: Strong programming skills in Python, C++, or similar languages.
• Bonus: Experience with distributed computing, optimizing AI models for real-world applications, and the ability to apply machine learning techniques to enhance business and user experiences; publications in top AI/ML conferences or strong contributions to open-source AI projects.