The algorithm team is responsible for developing state-of-the-art computer vision, NLP and multimodality models and algorithms to protect our platform and users from the content and behaviors that violate community guidelines and related regulations.
With the continuous efforts from our team, TikTok is able to provide the best user experience and bring joy to everyone in the world.
In our team, you will have the opportunity to participate in the development of the cutting-edge content understanding model to help improve the recognition ability of violated content in TikTok, and will also be responsible for optimizing our distributed model training framework continuously.
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.
* This opening is part of the general hiring process for the Data-TnS-Algo organization.
Applications will be evaluated by multiple teams within the Data-TnS-Algo organization to ensure the best alignment based on skills and interests.
Responsibilities:
- Leverage multimodal large models to explore few-shot and zero-shot strategies for content safety scenarios, and build moderation models with strong generalization capabilities.
- Participate in reinforcement learning–based data mining, and help design Chain-of-Thought (CoT) annotation frameworks to improve the model’s understanding of complex risks.
- Build risk ranking and recall systems to enhance coverage and accuracy in identifying high-risk content.
- Collaborate with product and policy teams to drive real-world deployment and performance optimization of moderation algorithms.