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 models5.
- 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
Minimum qualifications :
- Bachelor or advanced degree in computer science or a related technical discipline.
- Effective communication and teamwork skills.
- Proficient coding skills and strong algorithm & data structure basis. Preferred qualifications : - 3+ years of related industry experience.
- Experience in one or more of the following areas is preferred : NLP, LLM, RL- Candidates with top-tier conference papers, including ICML, NeurIPS, ICLR, CVPR, ICRA, KDD etc.
relevant internship experience or winners of ACM competitions are preferred;- Experience in using data-driven methods to enhance the capability of LLMs through various stages of the model development- Experience in RAG, Prompt Engineering or other inference time methods to enhance the performance of the system
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