To protect TikTok e-commerce users, including and beyond buyer, seller, creator; To make Tiktok e-commerce the safest and most trusted place worldwide to transact online by securing the integrity of the e-commerce ecosystem and providing a safe shopping experience on the platform.
Requirements
- Proficiency in modern machine learning theories and applications, including ensemble trees, deep neural networks, transfer/multi-task learning, reinforcement learning, graph theory, and unsupervised learning.
- Experience with Python, SQL/Hive, and Hadoop
- Strong understanding of data structures and algorithms, with excellent problem-solving ability
- Demonstrated software engineering experience from previous internship, work experience, coding competitions, or publications
- Internship experience or research experience, especially in e-commerce, risk control domian
- Curiosity towards new technologies and entrepreneurship
- High levels of creativity and quick problem-solving capabilities
Responsibilities
- Develop and implement innovative machine learning algorithms to manage business risks in TikTok's products and platforms.
- Prototype and explore novel solutions, conduct experiments to validate hypotheses, and provide insights to Product and Tech teams.
- Collaborate with multidisciplinary teams to enhance current automation processes.
- Build efficient data querying infrastructure for real-time and offline analysis.
- Identify opportunities to strengthen risk defense solutions.
- Define risk control metrics and promote data-driven practices.
- Document technical processes and effectively communicate results through writing, visualizations, and presentations.
Other
- Final year or recent graduate with a background in Computer Science, Computer Engineering, or a related technical discipline
- Detail oriented, effective time management, and strong analytical skills
- Successful candidates must be able to commit to an onboarding date by end of year 2026.
- Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.
- Applications will be reviewed on a rolling basis - we encourage you to apply early.
