PhD Machine Learning Intern, Ads Core ML Team

Job Description

About the Role
This PhD internship is with the TikTok Ads Core ML Team, focused on creating next-generation automatic ad delivery products and developing advertising as a global business. The team’s mission is to establish a world-leading ranking model and framework to benefit collaborators, users, and customers with better returns. Interns will actively contribute to products, research, and the organization’s future plans and emerging technologies through a dynamic experience that includes hands-on learning and collaboration with industry experts.

What You’ll Do
• 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.

You’re a Good Fit If You
• Are currently pursuing a PhD Degree in Computer Science, Mathematics, Statistics, or a related technical discipline with 2+ years research or machine learning modeling experience.
• Are able to commit to working for 12 weeks during Summer 2026.
• Have solid programming skills, proficient in C/C++ and Python.
• Are familiar with basic data structure and algorithms.
• Are familiar with Linux development environment.
• Have good analytical thinking capability.
• Have essential knowledge and skills in statistics.
• Have good theoretical grounding in deep learning concepts and techniques.
• Are familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet), familiar with its architecture and implementation mechanism.
• Are able to commit to at least 3 months long internship period.

Bonus Qualifications
• Are a PhD candidate focused on a statistical learning related field.
• Are graduating December 2026 onwards with the intent to return to degree program after the completion of the internship.
• Have good knowledge in one of the following fields: Factorization Machine, Uplift Modeling, Diffusion Models, Reinforcement Learning.
• Have a basic understanding of large recommendation system and ads serving system concepts.

Role Highlights & Compensation
• The hourly rate range for this position is $60- $60.
• Interns have day one access to health insurance, life insurance, wellbeing benefits and more.
• Interns receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year).
• Interns who are not working 100% remote may also be eligible for housing allowance.