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.

About the Team
Our team is pioneering the future of large language model-based applications with a focus on developing long-term memory capabilities and delivering personalized chat, search, and recommendation experiences. We're leveraging our deep expertise in artificial intelligence to create advanced AI algorithms that can understand, learn, and predict, dramatically enhancing user interactions. Our mission is to revolutionize how we engage with machines, making them more intuitive and human-like than ever. With a relentless commitment to excellence and a profound understanding of AI, we are setting new standards and pushing the boundaries of what language model-based applications can achieve.

Responsibilities：
- Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU)
- Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
- Leading a team from a technical perspective to develop ML best practices and influence engineering culture
- Be a go-to person to escalate the most complex online/production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
- Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
- Suggest, collect and synthesize requirements and create effective feature roadmap
- Code deliverables in tandem with the engineering team