Machine Learning Engineer Graduate (Lead Ads Technology) – 2026 Start (BS/MS)

Responsibilities

The Lead Ads team empowers TikTok’s global monetization (billion-dollar business) via efficiently delivering lead ads on TikTok. Our mission is to push the boundaries of large-scale ads delivery systems and lead the innovations of TikTok’s personalized online advertising. 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. Key Responsibilities • Build highly scalable machine learning systems and state-of-the-art machine learning models to improve ads ranking quality and optimize advertisers’ marketing strategies. Examples include but are not limited to click through rate prediction, conversion rate prediction, intelligent format selection and user journey optimization. • Explore, develop and experiment with new features to improve model accuracy. • Understand ads platform objectives and take full advantage of modern machine learning to improve ads relevance, quality, and quantity delivered to end-users. • Collaborate with Product Managers, Designers, and other disciplines to explore the next generation of shopping experiences on TikTok.

Qualifications

Minimum Qualifications: • BS/MS degree in Computer Science, Computer Engineering, or other relevant majors, with related work experience. • Solid programming skills, including but not limited to: Go, C/C++, Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment. • Good analytical thinking capability. Have essential knowledge and skills in statistics. • Good theoretical grounding in the machine and deep learning concepts and techniques (CNN/RNN/LSTM, etc.). • Familiar with the architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet), familiar with its architecture and implementation mechanism. Preferred Qualifications: • Good understanding in one of the following domains: ads bidding & auction, ads quality control, and online advertising systems (familiar with one or more of these terms: CPC/CPM, CTR/CVR, Ranking /Targeting, Conversion/Budget, Campaign/Creative, Demand/Inventory, DSP/RTB). • Experience in resource management and task scheduling with large-scale distributed software (such as Spark and TensorFlow). • Relevant work or research experiences in search and recommendation.

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