Data Scientist
Responsibilities:
- Design, implement, and optimize prompting and tuning techniques for Large Language Models (LLMs) and LLM-based agents.
- Develop and enhance the in-house AI training and inference platform to improve scalability and performance.
- Conduct cutting-edge research and development in LLMs, Retrieval-Augmented Generation(RAG), and agents.
- Collaborate with cross-functional teams to deploy LLMs and agents into production environments.
Requirements:
- Minimum Bachelor's Degree in Computer Science, Mathematics, Computational Linguistics, or a related field.
- 2+ years of hands-on experience in data science, machine learning, or AI research, with proficiency in Python.
- Strong understanding of NLP/CV/LLM fundamentals, including Transformers and Attention, etc.
- Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and related libraries (e.g., Hugging Face, LangChain).
- Having experience in fine-tuning large language models (LLMs) and developing LLM-based agents.
- Publications in top-tier conferences (NeurIPS, ICML, ACL, CVPR, etc.) are highly desirable.
- Having experience in applying AI techniques to solve financial problems is a plus.
- Excellent communication skills; both in written and spoken English.