TikTok
Machine Learning Engineer Intern (E-Commerce Recommendation Live)- 2027 Summer
Seattle, Washington, United States of America · Intern · Internship
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About the role
- Team Introduction: The Global E-commerce Recommendation Live Algorithm team is responsible for the core recommendation stack for live commerce, covering the full pipeline from recall and pre-ranking to ranking and mixed ranking.
- By combining generative recommendation, large recommendation models, multimodal representation learning, and cross-domain value modeling, the team works on some of the most important algorithmic problems in live commerce.
- Candidates may apply to a maximum of two positions across Our Company and its affiliates globally.
Responsibilities
- Build and optimize recommendation models across recall, pre-ranking, ranking, and mixed ranking to improve GMV, conversion, watch time, and long-term user value.
- Develop cross-domain and multimodal modeling solutions that connect videos, live streams, products, and user behavior to better power live commerce recommendations.
- Partner with cross-functional teams to launch scalable solutions, run experiments, and turn research into measurable business impact.
Requirements
- Strong analytical and problem-solving skills, with the ability to translate business problems into effective modeling solutions.
- Self-driven and results-oriented, with the ability to take ownership of model iteration and online impact from end to end.
- The team operates in a highly dynamic environment where live room status changes in real time, conversion signals are sparse, and user intent must be understood across content, commerce, and transaction scenarios.
Nice to have
- Experience in recommendation systems, especially in live commerce, e-commerce, search, ads, or other large-scale consumer products.
- Experience with generative recommendation, large recommendation models, retrieval and ranking systems, or related recommendation architecture upgrades.
- Publications in top-tier conferences such as NeurIPS, ICML, ICLR, KDD, ACL, CVPR, SIGIR, or RecSys, or strong achievements in major technical competitions.
Benefits
- Advance next-generation recommendation technologies, including generative recommendation, large recommendation models, reinforcement learning, and long-term value optimization.
Company info
- We are looking for talented individuals to join us for an internship.
This listing is sourced directly from TikTok's careers page and normalized into a canonical job model.