TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.
Why Join Us
Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.
Team Introduction
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 dynamic, fast-pacing, collaborative and impact-driven.
We are looking for talented individuals to join us for an internship in 2024. 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.
This Internship Program runs for 10-24 weeks. Candidates can also apply for both Off-cycle Intern position and Program Intern position.
Applications will be reviewed on a rolling basis. We encourage you to apply early. Candidates can apply to a maximum of TWO positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
1. Participate in the recommendation algorithm and make contributions to a world-class large scale recommendation system.
2. Optimize the core algorithms and strategies (recall, coarse ranking, fine ranking, mixed ranking, diversity, etc.) through modeling technologies including deep learning, representation learning, multi-task learning, causal inference, and sequence modeling.
3. Work closely with the product and operations team, excel in technological innovation with deep integration of business characteristics, and help achieve long-term and short-term business development goals.
