Responsibilities

Global E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-commerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, to provide the best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and large scale models. 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. Online Assessment Candidates who pass resume screening will be invited to participate in Our Company's technical online assessment. Responsibilities: This internship provides students the opportunity to join one of our engineering teams where you will have the opportunity to: - Build and maintain high performance online services for TikTok recommendation system. - Build extremely efficient and reliable data pipelines for candidates generation, profile generation, training examples generation, realtime online training, etc. - Work with your mentor to build globalized large-scale recommendation system. - Design and develop high performance computing frameworks and storage systems.

Qualifications

Minimum Qualifications: - Must be able to commit to a 12-week full-time work period during Summer 2027 - Currently pursuing an Undergraduate/Masters degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline. - Experience in programming, included but not limited to, the following programming languages: C, C++, Java or Golang. - Effective communication skills and a sense of ownership and drive. Preferred Qualifications: - Demonstrated software engineering experience from previous internship, work experience, coding competitions, or publications. - Demonstrated experience in one area of the following areas: personalized recommendations, search engine, machine learning, distributed storage system, big data frameworks is a plus. 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

Job Information

[For Pay Transparency]Compensation Description (Hourly) - Campus Intern

The hourly rate range for this position in the selected city is $42.75- $42.75.

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.