Responsibilities
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.
We're looking for innovative Research Engineer Interns focused on ML/RL/LLM or other relevant professional domains, to join our TikTok Ads Core ML Ranking team. Ads Core Ranking team specifically focuses on maximizing delivery system efficiency and revenue growth through state-of-the-art models and frameworks. Our research topics include but not limited to: Generative Retrieval and Large Recommendation Model, LLM-based Ranking Application, and Optimization of System Resource Allocation with ROI target.
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Internships at TikTok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. It runs for 12 weeks beginning in May/June 2025. Please state your availability clearly in your resume (Start date, End date).
Summer Start Dates:
Monday, May 12
Monday, May 19
Tuesday May 27 (Memorial Day May 26)
Monday, June 9
Monday, June 23
Applications will be reviewed on a rolling basis. We encourage you to apply early. Candidates can apply to a maximum of TWO positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally.
Responsibilities:
As part of our team, you will be responsible for:
- 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.
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
Qualifications
Minimum Qualifications:
- Currently pursuing a PhD Degree in Computer Science, Mathematics, Statistics, or a related technical discipline with 2+ years research or machine learning modeling experience.
- Able to commit to working for 12 weeks during Summer 2025.
- Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
- Good analytical thinking capability. Essential knowledge and skills in statistics.
- 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.
Preferred Qualifications:
- PhD candidate focused on a statistical learning related field.
- Graduating December 2025 onwards with the intent to return to degree program after the completion of the internship.
- 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.