Machine Learning Engineer Intern (Monetization Technology - Ads Core Global) - 2026 Summer (BS/MS)
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About this role
Introduction
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.
We are looking for talented individuals to join us for an internship in 2026. Internships at our company aim to offer students industry exposure and hands-on experience. Watch your ambitions become reality as your inspiration brings infinite opportunities at our company.
Internships at our company aims 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.
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 our company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).
Summer Start Dates:
- May 11th, 2026
- May 18th, 2026
- May 26th, 2026
- June 8th, 2026
- June 22nd, 2026
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.
Qualifications
Minimum Qualifications:
- Currently pursuing an Undergraduate/Master Degree in Computer Science, Mathematics, Statistics, or a related technical discipline.
- 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:
- 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.