Machine Learning Engineer Intern (Lead Ads) - 2027 Summer

Responsibilities

The Lead Ads team empowers TikTok's global monetization (billion-dollar business) via efficiently delivering lead ads on TikTok. Our mission is to push the boundaries of large-scale ads delivery systems and lead the innovations of TikTok's personalized online advertising.

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.

Responsibilities:
- Participate in the development of a large-scale Ads system
- Responsible for relevance model and strategy optimization, such as semantic matching models, active learning, text/photo/video multi-model, ranking strategy, etc
- Participate in the development and iteration of Ads algorithms by using Machine Learning.
- Work on NLP (Natural Language Processing) capability improvement and query understanding, such as query classification, seq2seq, NER (Named Entity Recognition), knowledge graph, bidword optimization, etc
- Work on CTR/CVR model estimation accuracy, data analysis, modeling, feature engineering
- Research and develop Ads pacing algorithms, ads traffic control, etc
- Partner with product managers and product strategy & operation team to define product strategy and features

Qualifications

Minimum Qualifications:
- Currently pursuing a Bachelor's or above degree in Computer Science, Computer Engineering, or a related technical discipline.
- 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.
- Must be able to commit to a 12-week full-time work period during Summer 2027.

Preferred Qualifications:
- Ads system, recommendation, searching, ranking, etc.