PhD ML Intern: Multimodal Recommendation Foundation

TikTok; San Jose (CA); Vor Ort; USD 68.000 - 97.000; Vollzeit

Benefits dieser Stelle

Health insurance

10 paid holidays per year

Housing allowance

Zusammenfassung

TikTok's Recommendation Foundation team within Data – Global E-commerce is building shared Foundation Models for diverse scenarios. We seek PhD interns to contribute to our research and products, with an emphasis on exploration and practical engineering impact.

Internships blend hands-on learning, community-building, and collaboration with industry experts. You will work on multimodal tokenizers, LLM-native recommendations, and end-to-end system development.

Qualifikationen

• Currently pursuing a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics or a related discipline.
• Solid foundation in machine learning and deep learning, with strong interest in LLMs and generative recommendation.
• Proficiency in Python and experience with deep learning frameworks such as PyTorch.
• Self-driven, with a strong research mindset and solid engineering skills.

Aufgaben

• Participate in the full training lifecycle of Recommendation Foundation Models, including pre‑training, mid‑training, and post‑training.
• Design and train multimodal semantic tokenizers for recommendation items, leveraging multimodal foundation models to encode rich item content into discrete semantic tokens and raise the performance ceiling of Recommendation Foundation Models.
• Develop LLM‑native recommendation by incorporating recommendation tasks directly into large language model training and leveraging world knowledge to improve recommendation quality.
• Build the next generation of recommendation systems powered by Recommendation Foundation Models, spanning retrieval, ranking, and end‑to‑end generative recommendation.

Kenntnisse

Python

PyTorch

ML/DL

Research mindset

Self-driven

Ausbildung

PhD in CS/EE/Math/Stats

Jobbeschreibung

TikTok's Recommendation Foundation team within Data – Global E-commerce is building shared Foundation Models for diverse scenarios. We seek PhD interns to contribute to our research and products, with an emphasis on exploration and practical engineering impact.

Internships blend hands-on learning, community-building, and collaboration with industry experts. You will work on multimodal tokenizers, LLM-native recommendations, and end-to-end system development.