Machine Learning Engineer Intern (TikTok-Data-Search-Basic Ranking) - 2027 Summer
TikTok
- Location
- San Jose, California, United States of America
- Employment
- Internship
- Work model
- On-Site
- Level
- Intern
- H-1B history
- 148 approvals (FY2023)
Skills
About this role
The Search team builds the systems that help users find relevant, reliable, and engaging content across TikTok. The team works across search retrieval, ranking, recommendation signals, query understanding, relevance, infrastructure, and product experiences. Our work combines large-scale machine learning, data-driven product development, and distributed systems to improve search quality for a global user base.
We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth.
Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.
Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted.
Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.
Responsibilities - Support the design, implementation, testing, and iteration of Search features, services, or tools under the guidance of engineers and mentors. - 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.