Machine Learning Engineer (Recommendation Alliance) Intern, TikTok Global E-Commerce - 2025 Start

t TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.

About the Team
The E-commerce alliance team aims to serve merchants and creators on the e-commerce platform to meet merchants' business indicators and improve creators' creative efficiency. By cooperating with merchants and creators, we aim to provide high-quality content and a personalized shopping experience for TikTok users, create efficient shopping tools at seller centers, and promote cooperation between merchants and creators.

We are looking for talented individuals to join us for an internship in from August 2024 onwards. 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

• Build and design large-scale machine learning algorithms to model the real-time interests of creators to improve conversion efficiency.
• Optimize TikTok's massive commodity relationship mining and ranking and recall of creators' product recommendations, and improve the overall GMV of the platform.
• Use the large scale of data to deeply analyze the behavior of creators and merchants and build targeted algorithm strategies to empower creators and merchants, improve merchants' monetization efficiency, and boost industrial upgrading.
• Support the rapid development of TikTok's e-commerce business, serve millions of merchants, explore more efficient business models, satisfy users with the best shopping experience, and promote ecological development.
• Support the production of scalable and optimised AI/machine learning (ML) models.
• Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models.

Qualifications

Minimum Qualifications

• Undergraduate, or Postgraduate who is currently pursuing a degree/master in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Solid theoretical understanding of machine learning, with familiarity with algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, and Deep Neural Networks.
• Experience in training and deploying models using frameworks like PyTorch, TensorFlow, or MXNet.
• Strong learning ability, with excellent communication and teamwork skills.

Preferred Qualifications

• Publications at conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI, RecSys, and similar.
• Practical Experience: Experience from internships, research, or projects, especially in fields like e-commerce, recommendations, or search engines.
• Problem Solving and Creativity: Passionate about technology and solving challenging problems, with high levels of creativity and quick problem-solving capabilities.

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy.

If you have any questions, please reach out to us at [email protected].