Machine Learning Engineer Intern - E-Commerce Recommendation Live - 2027 Start - PhD

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. 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. By combining generative recommendation, large recommendation models, multimodal representation learning, and cross-domain value modeling, the team works on important algorithmic problems in live commerce. Its goal is to improve user experience, optimize ecosystem efficiency, and drive sustainable business growth for TikTok Shop across global markets. PhD internships provide students with the opportunity to contribute to products, research, future plans, and emerging technologies. The internship experience combines hands-on learning, community-building and professional development events, and collaboration with industry experts. Applications are reviewed on a rolling basis. Applicants should clearly state their availability, including start and end dates, in their resume. ## 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. - Advance next-generation recommendation technologies, including generative recommendation, large recommendation models, reinforcement learning, and long-term value optimization. - Partner with cross-functional teams to launch scalable solutions, run experiments, and turn research into measurable business impact. ## Minimum Qualifications - Currently pursuing a PhD in Computer Science, Engineering, Operations Research, or a related technical discipline. - Solid foundation in machine learning and at least one of the following areas: recommendation systems, search, advertising, NLP, multimodal learning, or large-scale applied AI. - Strong programming skills in Python or C++, and hands-on experience with deep learning frameworks such as PyTorch. - Good understanding of data structures, algorithms, and large-scale model training or production machine learning systems. - 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. ## Preferred Qualifications - 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. - Experience with LLMs or multimodal foundation models, including pre-training, post-training, representation learning, contrastive learning, SFT, or RL-based optimization. - Experience in cross-domain transfer learning, LTV modeling, long-term value optimization, causal inference, or debiasing. - Experience with long-sequence user behavior modeling, multi-task learning, multi-interest modeling, or large-scale distributed training and inference optimization. - Publications in top-tier conferences such as NeurIPS, ICML, ICLR, KDD, ACL, CVPR, SIGIR, or RecSys, or strong achievements in major technical competitions. - Strong curiosity about new technologies, fast learning ability, and a passion for solving challenging real-world problems. ## Compensation and Benefits The hourly rate range for this position in the selected city is $57–$57. Interns have day-one access to health insurance, life insurance, wellbeing benefits, and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in the first half of the year, 40 hours if hired in the second half). Interns who are not working 100% remotely may also be eligible for a housing allowance. Benefits may vary depending on the nature of employment and country work location. ## About TikTok TikTok is the leading destination for short-form mobile video. Its mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, with offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.