Machine Learning Engineer Intern (E-Commerce Recommendation Foundation) - 2027 Start (PhD）

This internship is with the Recommendation Foundation team within TikTok’s Data – Global E-commerce organization, focused on building shared Recommendation Foundation Models across scenarios. The team explores an event-sequence-driven generative recommendation paradigm integrating large language and vision-language models (LLMs/VLMs), multimodal understanding, reinforcement learning, and system optimization. The goal is to advance recommendation systems beyond click prediction toward general-purpose recommendation agents, emphasizing the understanding of relationships between people and content to generate new connections. The team values original exploration, research thinking, and engineering practice in an open environment where members can propose and validate ideas.

About the role

PhD internships at TikTok provide students with the opportunity to actively contribute to products and research, shaping the organization's future plans and emerging technologies. The internship blends hands-on learning, community-building, professional development, and collaboration with industry experts.

Responsibilities

• 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.

Requirements

Minimum Qualifications

• Currently pursuing a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related discipline.
• Solid foundation in machine learning and deep learning, with a 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.

Preferred Qualifications

• Experience with pre-training, mid-training, or post-training of LLMs or Foundation Models.
• Research or project experience in generative recommendation, LLM-native recommendation, or multimodal semantic tokenization.
• Publications on LLM-related topics at top-tier machine learning or natural language processing conferences, such as NeurIPS, ICML, ICLR, ACL, EMNLP, or NAACL, or strong achievements in major technical competitions.

Pay

The hourly rate for this position is $60.

Benefits

• Day one access to health insurance, life insurance, and wellbeing benefits.
• 10 paid holidays per year.
• Paid sick time (56 hours if hired in the first half of the year, 40 if hired in the second half).
• Eligibility for housing allowance (for interns not working 100% remote).