TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, 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.

Our Trust and Safety RD team is fast growing and responsible for building machine learning models and systems to identify and defend internet abuse and fraud on our platform. Our mission is to protect billions of users and publishers across the globe every day. We embrace the state-of-the-art machine learning technologies and scale them to detect and improve the tremendous amount of data generated on the platform. With the continuous efforts from our team, TikTok is able to provide the best user experience and bring joy to everyone in the world.

We are looking for people like you with solid experience in designing and deploying state-of-the-art models in the combination of NLP and CV related areas. This position will work with a team of excellent research scientist and machine learning engineer who can take initiatives, design and develop advanced machine learning solutions, and deploy them directly to TikTok's global platform.

Responsibilities - What You'II Do
• Work with team members to design next generation CV/NLP/Audio multimodality models
• Work on highly-scalable classifiers, predictive models and algorithms in big data mining, computer vision, NLP and other domains
• Work with engineering teams to implement model pipeline and deploy the service at scale
• Collaborate with product team to define objectives and improve trust and safety strategy
• Collaborate with data analyst to understand and find data patterns