About the role#
The Global E-commerce Recommendation Live Algorithm team manages the core recommendation stack for live commerce. This includes the full pipeline from recall and pre-ranking to ranking and mixed ranking. You will work in an environment where live room status changes in real time and user intent spans content, commerce, and transaction scenarios. This internship provides the opportunity to contribute to products and research while collaborating with industry experts.
What you'll do#
- 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 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.
What you'll need#
- Currently pursuing a PhD in Computer Science, Engineering, Operations Research, or a related technical discipline.
- Solid foundation in machine learning with experience in at least one area: 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.
- Preferred experience includes work in live commerce, generative recommendation, LLMs, multimodal foundation models, long-sequence user behavior modeling, or causal inference.
- A track record of publications in top-tier conferences such as NeurIPS, ICML, ICLR, KDD, ACL, CVPR, SIGIR, or RecSys is a plus.
Location & details#
- Location: San Jose, California, United States.
- Employment type: Full-time intern.
- Compensation: $60 per hour.
- Program: PhD Intern, 2027 start.
- Modality: On-site.
- Applications are reviewed on a rolling basis.
About TikTok
TikTok operates as an entertainment provider. The company maintains a global presence with offices in cities including Los Angeles, Singapore, New York, London, and Tokyo. It employs over 92,000 people. The organization is privately held.
How to get in at TikTok
Landing an internship at TikTok requires speed because early applicants often get seen before the pile grows. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you can apply among the first. This gives you a better chance of your resume being reviewed while the team is still actively filling the position. You should aim to be one of the first people to submit your materials. Reaching out to the right person can also improve your chances of getting a response. Intern Insider surfaces the recruiters behind the company roles so you can contact them directly to ask about the role or a referral. This direct approach often works better than waiting for a response from a general application queue.
