The Content Ecology Algorithm Team at TikTok is focused on driving AI innovations in areas like LLMs, NLP, Computer Vision, multimodal learning, and recommendation algorithms to power various business lines including Local Services, Search, Core Video Architecture, Professional Content (PGC), and User Growth (UG). The team aims to enhance user engagement and TikTok's growth through AI-driven solutions.
Requirements
- Strong programming skills in Python, C++, or similar languages.
- Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.
- Solid understanding of machine learning, NLP, CV, or recommendation algorithms.
- Experience with distributed computing and optimizing AI models for real-world applications.
- Ability to apply machine learning techniques to enhance business and user experiences.
- Publications in top AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.) or strong contributions to open-source AI projects.
Responsibilities
- Develop and optimize LLM, NLP, CV, and recommendation models to improve TikTok’s content ecosystem.
- Implement multimodal AI solutions, integrating video, text, and speech understanding.
- Optimize LLM-powered search, discovery, and content recommendation systems for better user engagement.
- Train and fine-tune deep learning models using TensorFlow, PyTorch, or other ML frameworks.
- Deploy and scale machine learning solutions in a distributed computing environment.
- Work closely with AI researchers, software engineers, and business teams to apply AI technologies effectively.
Other
- PhD in Computer Science, Machine Learning, AI, or a related field.
- Internships at TikTok aim to offer students industry exposure and hands-on experience.
- PhD internships at TikTok provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies.
- 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).
