TikTok Ads Core ML Team aims at creating automatic delivery products for the next generation and developing advertising as a global business, instead of just a monetization tool to consolidate the delivery funnel framework allowing multiple teams to iterate parallel. All of our team effort, is to continuously pursue and establish a world-leading ranking model & framework that always benefits our collaborators, users and customers to get better returns.
Requirements
- Currently pursuing a PhD Degree in Computer Science, Mathematics, Statistics, or a related technical discipline with 2+ years research or machine learning modeling experience.
- Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
- Good theoretical grounding in deep learning concepts and techniques.
- Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet), familiar with its architecture and implementation mechanism.
- PhD candidate focused on a statistical learning related field.
- Good knowledge in one of the following fields: Factorization Machine, Uplift Modeling, Diffusion Models, Reinforcement Learning.
- Basic understanding of large recommendation system and ads serving system concepts.
Responsibilities
- Assist in optimizing efficiency across the entire advertising funnel, including Recall&Rough-sort, Fine-sort(CTR/CVR), format/creative personalization and system resource allocation.
- Research & develop a global advanced advertising delivery system through frontier technologies, including ML/DL, RL, LLM and also scaling law in ads recommendation.
- Design & Set up system framework and standard to continuously improve overall efficiency and meet different vertical business needs.
- Work with product and business teams from various scenarios with global impact.
Other
- Able to commit to working for 12 weeks during Summer 2026.
- Good analytical thinking capability.
- Essential knowledge and skills in statistics.
- Graduating December 2026 onwards with the intent to return to degree program after the completion of the internship.
- Successful candidates must be able to commit to at least 3 months long internship period.
