Machine Learning Engineer Graduate (Ads Interface and Platform) - 2026 Start (BS/MS)

We are TikTok Monetization Ads Interface Team, dedicated to creating an exceptional advertising experience and intelligent growth marketing strategies for global advertising clients. Here, you will engage with challenging technical domains such as large-scale user systems, diverse advertising fields (ad creation, material optimization, delivery strategy, attribution, measurement, etc.), AI-driven personalized recommendations and growth strategies, and massive client profiling powered by LLM and big data. We are seeking like-minded individuals to join us in leveraging technology to help global small and medium-sized business (SMB) advertisers effectively connect with customers, achieve business success, and drive the rapid growth of TikTok's advertising business!

We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resumes.

Applications will be reviewed on a rolling basis. We encourage you to apply early.

Responsibilities:
1.Shape TikTok Monetization's growth through the development of personalized strategies such as coupons, internal advertising, and intelligent suggestions. This role directly influences the company's P&L and monetization roadmap.
2.Work with cross-functional teams to design cutting-edge machine learning models aimed at enhancing SMB advertisers' performance. This includes predicting key performance indicators like click-through rates and conversion rates, leveraging data and technology to drive business outcomes.
3.Build TTAM (TikTok Ads Manager) Copilot by integrating LLMs into our products and services to improve advertiser engagement. Tasks include developing Generative-AI based QAs, recommending auto-creation strategies, and developing conversational creation flows, all contributing to user satisfaction and engagement.