Senior Research Engineer, TikTok AI Search (LLM Pretraining/Alignment/Inference)

Job Description
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
On the TikTok Search Team, you will have the opportunity to develop and apply cutting edge machine learning technologies in real-time large-scale systems, which serve billions of search requests every day. Via advanced NLP and multi-modal models, our projects impact and improve the search experience for hundreds of millions of users globally. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.

The main job directions include:
1. Exploring and developing large-scale language models and optimizing enterprise applications to the extreme;
2. Data construction, instruction tuning, preference alignment, and model optimization;
3. Implementation of relevant applications, including content generation, summary etc.;
4. Collaborating with cross-functional teams to produce and apply new science to more responsibly develop and deploy large language models
5. In-depth research and exploration of more usage scenarios in future life.

Responsibilities:
- Conduct research and develop state-of-the-art algorithms in various stages of the development of LLM, including continued pretraining, SFT, RLHF;
- Investigate and implement robust evaluation methodologies to assess model performance at various stages, unravel the underlying mechanisms and sources of their abilities, and utilize this understanding to drive model improvements.
- Using inference stage techniques such as RAG, CoT, Prompt Engineering to improve the model output
- Improve the performance of AI Search in the TikTok app to provide better search experience for users