Responsibility

• Develop and optimize Large Language Models (LLMs) application pipelines, including data preparation, prompt engineering, inference and response post-processing.
• Design and build robust LLM-based agents, including tool-use capabilities, planning and memory modules.
• Develop and manage knowledge base and Retrieval-Augmented Generation (RAG) systems for domain-specific information retrieval.
• Collaborate actively with IT, risk, business departments, and external vendors to ensure smooth project advancement.
• Explore and drive the application of new technologies in business operations to promote innovative practices in AI technology.

Requirements:

• Bachelor’s degree or higher in Computer Science, Computer Engineering, Information Systems, Statistics, Applied Mathematics.  
• Strong proficiency in programming languages such as Python and familiarity with relevant libraries (e.g., PyTorch, Tensorflow, Hugging Face Transformers).
• Proven experience in developing and deploying application using Large Language Models (LLMs).
• Essential abilities in prompting, context engineering, and fine-tuning techniques.
• Experience in developing LLM-based agents and knowledge base/RAG systems.
• Familiarity with model efficiency techniques like LoRA (Low-Rank Adaptation) and knowledge distillation.