Machine Learning Scientist Graduate (Global Monetization Technology) - 2026 Start (PhD)
Skip the busywork
ApplyBolt rewrites your resume for this exact role and hits submit. You just pick the jobs.
About this role
Monetization 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 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.
What You'll Do:
- 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.
Qualifications
Minimum Qualifications:
- Final year Ph.D or recent Ph.D graduates in computer science, machine learning, or similar fields.
- 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.