[Remote] Machine Learning Engineer Intern (Monetization Technology - Ads Creative) - 2026 Start (BS/MS)

Note: The job is a remote job and is open to candidates in USA. TikTok is the leading destination for short-form mobile video, and they are seeking a Machine Learning Engineer Intern for their Monetization Technology team. The role focuses on enhancing ad creative understanding and optimization through innovative tech solutions, providing hands-on experience in a dynamic environment.

Responsibilities

• Assist in utilizing algorithms to better understand advertisers, creators, and creatives, improving precision in match-making processes
• Contribute to online modeling of large-scale commercial traffic, optimizing the distribution strategy of creatives within the recommendation and ads systems
• Help develop allocation strategies for both natural and ads traffic, aimed at increasing both short-term and long-term value for advertisers and creators
• Collaborate with senior engineers to implement and test new algorithms that enhance the accuracy of content recommendations
• Participate in analyzing large datasets to identify trends and patterns, providing actionable insights for improving the ad targeting strategy
• Support the development of performance metrics to track the effectiveness of ad and creative distribution strategies
• Conduct experiments to validate new algorithms and strategies, ensuring scalability and efficiency in production systems
• Contribute to continuous optimization of machine learning models for better performance across diverse traffic and creative data
• Assist in preparing and presenting reports on model performance and recommendations to stakeholders

Skills

• Currently pursuing a Bachelor's degree or higher in Computer Science or a related field
• Research/internship experience or coursework in machine learning (e.g., RecSys, NLP, CV, GE), with a preference for candidates with exposure to recommendation systems
• Solid understanding of data structures and algorithms, with proficiency in at least one programming language (e.g., Python, C++, Golang)
• Strong interest in exploring new technologies, with a demonstrated ability to analyze problems and find solutions
• Good communication skills, with an eagerness to collaborate within a team and learn from peers
• Strong enthusiasm for contributing to business growth and willingness to take on challenges in a dynamic environment
• Previous internship or research experience in machine learning/deep learning, with a focus on recommendation systems, or advanced ranking solution strategies like RAG/LoRA/MoE etc
• Familiarity with large-scale data processing and distributed systems
• Exposure to reinforcement learning or deep learning techniques for optimizing recommendation systems
• Knowledge of A/B testing and other experimental design techniques to evaluate algorithm performance
• Strong interest in content personalization and ad optimization technologies
• Experience with model deployment or working in production environments

Benefits

• Interns have day one access to health insurance
• Life insurance
• Wellbeing benefits and more.
• Interns also receive 10 paid holidays per year
• 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.

Company Overview

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