(General Hire) Machine Learning Engineer Intern (Performance Monetization) - 2027 Summer

Global Monetization Product and Technology teams are building the next-generation monetization platforms to help millions of customers grow their businesses, utilizing our products like TikTok. Our team develops a wide variety of advertisements for numerous uses including feeds, live streaming, branding, measurement, targeting, search, vertical solutions, creative solutions, and business integrity.

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.

What is the General Hire? If you're applying under the General HIre track for the GMPT-Performance Monetization organization, your resume will be reviewed by all the subteams, and we'll help identify one or more teams that are the best match for you.

Why General Hire? This process gives you broader exposure and increases your chances of finding the right team fit!

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, Software Engineering, 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.

Preferred Qualifications:

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