Machine Learning Engineer Intern (E-Commerce) - 2027 Start (PhD)

About the team

TikTok E-commerce is a content-driven business powered by short-form video and live-streaming, dedicated to becoming the premier destination for users to discover affordable, high-quality products. Our team strives to deliver a tailored and efficient shopping experience while upholding a robust governance and risk control framework to ensure platform integrity, merchant compliance, and a secure ecosystem.

We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.

Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.

Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date).

Responsibilities

• Work with large-scale data, logs, metrics, or experiments to understand user search behavior and improve product or system quality.
• Collaborate with engineering, product, data science, and machine learning partners to define requirements and deliver project milestones.
• Write clear, maintainable code and documentation for assigned workstreams.
• Communicate progress, risks, and learnings with mentors and stakeholders throughout the internship.

Minimum Qualification(s)

• Currently pursuing a PhD degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field.
• Able to commit to a 12-week internship during Summer 2027.
• Proficient coding skills and strong algorithm & data structure basis.
• Effective communication and teamwork skills.

Preferred Qualifications

• Familiar with machine learning frameworks such as scikit-learn, tensorflow, pytorch.
• Ability to think critically, rationally, and communicate in result-oriented, data-driven manner.