Machine Learning Engineer Intern (App Ads and Gaming) - 2027 Summer

The App Ads and Gaming team empowers TikTok's global monetization (billion-dollar business) via efficiently delivering application ads on TikTok. Our mission is to push the boundaries of large-scale ad delivery systems and lead the innovations of TikTok's personalized online advertising.

We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth.

Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.

Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted.

Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.

Responsibilities:

• Participate in the development of a large-scale Ads system.
• Responsible for the development of state-of-the-art applied machine learning projects.
• Own key targeting components or strategies in the TikTok ads monetization ecosystem.
• Work with product and business teams on product vision. Minimum Qualifications:
• Currently pursuing a Bachelor's or above degree in Computer Science, Computer Engineering, or a related technical discipline.
• Experience in and good theoretical grounding in machine learning concepts and techniques.
• Excellent programming, debugging, and optimization skills in one or more general purpose programming languages, including but not limited to: Go, C/C++, Python.
• Experience in one or more of the following frameworks: Tensorflow/PyTorch/MXNet, etc
• Ability to think critically and to formulate solutions to problems in a clear and concise way.
• Must be able to commit to a 12-week full-time work period during Summer 2027.

Preferred Qualifications:

• Familiar with Ads system, recommendation, searching, ranking, etc.