ML Engineer Intern: Build Recs & Search Systems

TikTok USDS Joint Venture; San Jose (CA); On-site; USD 51,000 - 73,000; Full time

Benefits offered by this job

Health insurance

Life insurance

Wellbeing benefits

10 paid holidays

Housing allowance

Job summary

TikTok USDS Joint Venture LLC is seeking interns to design, build, and evaluate machine learning models for recommendation and search systems, with an emphasis on privacy, data governance, and security for US users.

The internship runs for 12 weeks in Summer 2027. Ideal candidates are pursuing a BS in a technical field, have strong coding skills, and can commit to an in-person schedule. Opportunities for learning and professional growth are offered along with social events and workshops.

Qualifications

• Currently pursuing a Bachelor's 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.

Responsibilities

• Design, build, train, and evaluate machine learning models for recommendation systems or search ranking.
• Implement efficient pipelines for feature extraction, model training, evaluation, offline-to-online deployment, and A/B testing.
• Process and analyze massive user behavior data and catalog logs using distributed systems to construct real-time and offline features.

Skills

Coding skills

Algorithms & data structures

Communication skills

Teamwork

Education

Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or related field

Master's degree in Computer Science, Computer Engineering, Software Engineering, or related field

Tools

scikit-learn

TensorFlow

PyTorch

Job description

TikTok USDS Joint Venture LLC is seeking interns to design, build, and evaluate machine learning models for recommendation and search systems, with an emphasis on privacy, data governance, and security for US users.

The internship runs for 12 weeks in Summer 2027. Ideal candidates are pursuing a BS in a technical field, have strong coding skills, and can commit to an in-person schedule. Opportunities for learning and professional growth are offered along with social events and workshops.