Responsibilities
About the Team
Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven.
We are looking for talented individuals to join us for an internship from August 2025 onwards. 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.
Applications will be reviewed on a rolling basis. We encourage you to apply early. Successful candidates are expected to work with the team for at least 12 weeks during the internship
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Responsibilities:
- Deploy, prompt, and optimize cutting-edge foundation models (eg. Large Language Models, LLM).
- Apply foundation models to enhance and optimize TikTok's recommendation system and product offerings, improving the experience of billion-scale consumers and creators.
- Collaborate with cross-functional teams, including product managers, data scientists, and product engineers, to form and solve problems, refine machine learning algorithms, and communicate results.
- Regularly run A/B tests, perform analyses, and iterate algorithms based on results.
- Work with infrastructure teams on improving the efficiency and stability of machine learning systems.
Qualifications
Minimum Qualifications:
- Currently pursuing PhD Degree.
- Hands-on experience in one or more of the following areas: Large Language Models (LLM), Machine Learning, Deep Learning, Recommender Systems, Data Mining, or Natural Language Processing
- Strong programming skills in Python and/or C/C++, and a deep understanding of data structures and algorithms
- Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet)
- Excellent communication and teamwork skills, and a passion for learning new techniques and tackling challenging problems
Preferred Qualifications:
- Prior research/industry experience with deploying, prompting, and fine-tuning foundation models
- Prior research/industry experience with applied machine learning, or large-scale recommendation systems
- Publications at major AI-related conferences such as NeurIPS, ICML, ICLR, AAAI, IJCAI, ACL, NAACL, EMNLP, CVPR, ICCV, ECCV, KDD, ICDM, SDM, RecSys, or simply on arXiv but with large impact
- Strong track record in AI-related competitions, or participation in public/open-source AI-related projects of high visibility