General Hire) Machine Learning Engineer Intern (-Recommendation) - 2027 Summer San Jose

(General Hire) Machine Learning Engineer Intern (Tik Tok-Recommendation) - 2027 Summer

Location:

San Jose

Intern

A64188B

Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven.

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.
* This opening is part of the general hiring process for the Tik Tok Recommendation organization. Applications will be evaluated by multiple teams within the Recommendation organization to ensure the best alignment based on skills and interests.

In this role, you'll have the opportunity to:

• Drive the development of industry-leading recommendation systems that elevate user experience, strengthen platform safety, and empower a vibrant content ecosystem.
• Deliver impactful, end-to-end machine learning solutions that tackle high-priority product challenges related to content understanding, LLMs, robustness, and fairness.
• Own and optimize the full-stack ML pipeline—from algorithm design to system infrastructure—to continuously push the boundaries of recommendation performance.
• Collaborate with cross-functional teams to craft innovative product strategies and develop intelligent solutions that fuel Tik Tok's growth in key global markets.

• Currently pursuing a Master degree with a background in computer science, machine learning, or similar fields.
• Good knowledge of theoretical and empirical research in addressing research problems.
• Solid knowledge and experience with at least one popular deep learning framework (e.g., PyTorch,Tensor Flow) and familiarity with deep neural network architectures.
• Able to commit to working for 12 weeks during Summer 2027.

• Research experience in one or more of the following fields: applied machine learning, machine learning infrastructure, large-scale recommendation system, market-facing machine learning product.
• Strong first-author publications record in top AI conferences or journals(e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.).
• Proficient in C/C++, Python, and shell programming languages, and have a deep understanding of data structure and algorithm design.
• Internship experience in an AI research organization.

For Tik Tok By  submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here:

The hourly rate range for this position in the selected city is $45- $45.

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.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including…