Machine Learning Engineer Intern (TikTok Shop Global E-Commerce, User Growth & Intelligent Marketing) - 2026 Start (BS/MS)

The team is responsible for algorithm and big data work on e-commerce innovation projects. Leveraging on our products, the team helps users discover and acquire great products, enriching their lives. In this team, we not only use recommendation and search algorithms to help users find items they are interested in but also employ risk control algorithms and intelligent platform governance algorithms to detect violations, ensuring a secure shopping experience. We build intelligent customer service technologies and large-scale product knowledge graphs to improve the efficiency of various transaction processes. Furthermore, we develop logistics and operations research algorithms to enhance supply chain efficiency, and we apply artificial intelligence to help merchants improve their operational capabilities. Our mission: To make high-quality products easily accessible, enabling everyone to enjoy a better life.

We are looking for talented individuals to join us for an internship in 2026. Internships at TikTok aim to offer students industry exposure and hands-on experience. Watch your ambitions become reality as your inspiration brings infinite opportunities at TikTok.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally.

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

Successful candidates must be able to commit to at least 3 months long internship period.

Responsibilities
- Participate in optimizing TikTok e-commerce growth and marketing algorithms, including core capabilities such as user value modelling, personalized messaging, recommendations, and intelligent marketing.
- Establish a user lifecycle data and value system to address core pain points and business challenges related to TikTok Mall user growth.
- Contribute to the implementation of product and technical solutions for user growth engines, such as personalized push notifications/emails, recommendation handling, etc., to increase e-commerce DAU and penetration rates.
- Optimize algorithms related to recall/sorting for new user recommendations, improving the relevance of traffic source handling and the accuracy and diversity of new user recommendations.
- Optimize intelligent marketing algorithms, utilizing uplift models and operations research methods to improve marketing efficiency and drive e-commerce GMV growth.