Machine Learning Engineer Intern (Creative AI) - 2025 Summer (BS/MS)

The TikTok Ads Creative & Ecosystem team's mission is to solve the above dilemma, by building industry-leading tech solutions for ads creative/landing page understanding, production/generation, and optimization, to inspire and empower advertisers, creators, and other 3rd parties in the ecosystem to create and deliver the best engaging creative experiences to the end users. Our work is at the core of TikTok and creator monetization. Examples of our team's work include TikTok video editor, AI-powered smart video generation (we are also exploring AIGC), and TikTok creative exchange (a creative marketplace to connect TikTok advertisers with creators or third-party creative agencies).

We are looking for talented individuals to join us for an internship in 2025. Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at TikTok.

Internships at TikTok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. It runs for 12 weeks beginning in May/June 2025 . Successful candidates must be able to commit to one of the following summer internship start dates below:
- Monday, May 12
- Monday, May 19
- Tuesday May 27 (Memorial Day May 26)
- Monday, June 9
- Monday, June 23

Please state your availability clearly in your resume (Start date, End date).

Responsibilities:
• Participate in the development of a large-scale Ads system.
• Participate in the development and iteration of Ads algorithms by using Machine Learning, including ads query understanding, ads targeting, ads ranking, model serving reliability, etc. Explore, develop and experiment with new features to improve model accuracy.
• Partner with product managers and the product strategy & operation team to define product strategy and features.Minimum Qualifications:
•Currently pursuing a BS/MS degree in Computer Science, Computer Engineering or other relevant majors.
• Solid programming skills, including but not limited to: Go, C/C++, Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
• Good analytical thinking capability. Have essential knowledge and skills in statistics.
• Good theoretical grounding in the machine and deep learning concepts and techniques (CNN/RNN/LSTM, etc.).
• Familiar with the architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet), familiar with its architecture and implementation mechanism.
• Strong communication and teamwork skills.
• Passion about technologies and solving challenging problems.

Preferred Qualifications:
• Strong understanding of recommender systems, including collaborative filtering, content-based methods, matrix factorization, and deep learning approaches, as well as key metrics (e.g., CTR, CVR, ROI) and personalization techniques in online model prediction.
• Experience with large-scale data processing and machine learning frameworks (e.g., TensorFlow, PyTorch, Spark, or Hadoop) to build and deploy scalable recommendation models.
• Proficiency in programming with C++, Python, and Golang to develop high-performance recommendation engines, optimize system performance, and build scalable backend services.
• Strong data analysis and model debugging abilities, including diagnosing model performance issues, analyzing user behavior data, and improving system effectiveness based on insights from A/B testing and offline evaluation metrics.