Software Engineer, Inference Optimization - Trust and Safety

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.



The Trust and Safety(TnS) engineering team is responsible for protecting our users from harmful content and abusive behaviors. With the continuous efforts of our trust and safety engineering team, TikTok can provide the best user experience and bring joy to everyone in the world. Our team is responsible for achieving goals by building content moderation process systems, rule engine, strategy systems, feature engine, human moderation platforms, risk insight systems and all kinds of supportive platforms across TnS organization.



Responsibilities:

- Work closely with business teams to optimize the integration plan for algorithm applications, improve efficiency in evaluating and using algorithm applications across various business scenarios, and reduce the cost of managing and optimizing algorithm applications in different business scenarios.

- Responsible for the architectural design, development, and performance tuning of algorithm applications, solving technical challenges such as high concurrency, high reliability, and high scalability. Work includes multiple sub-areas: ML model training and evaluation, model optimization, model inference, model management, dataset management, workflow orchestration, etc.

- Responsible for the design and development of Machine Learning infrastructure for LLM/AIGC, etc

- Responsible for researching and implementing cutting-edge engineering technologies related to LLM, NLP, CV.