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. Our Trust and Safety team is fast growing and responsible for building machine learning models and systems to protect our users from the impact of negative content. 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 moderate 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.

As a University Graduate Machine Learning Engineer, you'll have the chance to work with our clients and teams to address key business problems and identify areas of growth for the company. With your education and experience, you will be able to take on real-world challenges from day one.

Responsibilities
- Work with our world-class engineers to build content understanding models for content moderation.
- Work on state-of-the-art content understanding techniques including but not limited to unimodal/multimodal content classifiers, graph models, representation learning models, and LLM.
- Collaborate with product teams to define business objectives and improve trust and safety strategy.
- Collaborate with engineering teams to deploy machine learning models, design online model workflow, and implement serving pipeline at scale.
- Collaborate with data scientist team to understand the key challenges and propose data-driven strategies.