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.