Machine Learning Engineer Intern (Recommendations and Search)

Location: San Jose, United States; fully in-person schedule up to 5 days a week

Salary: $45 per hour

Company

hirify.global Joint Venture develops and operates TikTok-related products with a focus on U.S. user data security, privacy compliance, cybersecurity, reliability, and trust and safety.

What you will do

• Design, build, train, and evaluate machine learning models for recommendation systems and search ranking.
• Develop pipelines for feature extraction, model training, evaluation, offline-to-online deployment, and A/B testing.
• Process large-scale user behavior data and catalog logs using distributed systems.
• Construct real-time and offline features for personalized, high-performing user experiences.
• Work on machine learning solutions supporting recommendation engines, search relevance, and e-commerce systems.

Requirements

• Currently pursuing a bachelor's degree in computer science, computer engineering, software engineering, or a related technical field.
• Available for a 12-week internship during Summer 2027.
• Proficient coding skills and a strong foundation in algorithms and data structures.
• Effective communication and teamwork skills.
• Availability dates must be clearly stated on the resume.

Nice to have

• Currently pursuing a master's degree in a related technical field.
• Experience with recommendation systems, online advertising, information retrieval, natural language processing, machine learning, or large-scale data mining.
• Familiarity with scikit-learn, TensorFlow, or PyTorch.
• Critical, rational, and data-driven approach to problem solving and communication.

Culture & Benefits

• Hands-on experience and exposure to real-world machine learning challenges.
• Social events, learning programs, and development workshops.
• Health insurance, life insurance, and wellbeing benefits from the first day.
• Ten paid holidays per year and paid sick time.
• Housing allowance may be available for interns who are not working 100% remotely.