Information Technology (IT) - 資訊科技

全職 Full-time

talent.gov.hk

system

Automated Systems (HK) Ltd

Job Responsibilities:

<ul><li>Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation in conversational AI systems.</li>
	<li>Build and deploy intelligent AI agents capable of handling multi-turn conversations, executing autonomous tasks, integrating external APIs, and managing tool invocation based on user intent and context.</li>
	<li>Design and deploy a Model Context Protocol that facilitates seamless, standardized connectivity and data sharing between AI systems and external platforms, APIs, and databases.</li>
	<li>Use &amp; build vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts.</li>
	<li>Fine-tuned and optimized use of large language models.</li>
	<li>Implement and experiment with powerful NLP, NLU, and NLG techniques to enhance the capabilities and performance of our conversational AI products.</li>
	<li>Conduct research and stay abreast of the latest advancements in machine learning, NLP, and conversational AI to drive innovation and maintain competitive advantage.</li>
	<li>Oversee the implementation of AI, Data and Robotic projects</li>
	<li>Drive AI adoption for the company, translating AI capabilities into practical applications</li>
</ul>Job Requirements

<ul><li>Doctoral degree in computer science, Artificial Intelligence, Machine Learning, or a related field.</li>
	<li>5+ years of experience in machine learning engineering, with a focus on building and deploying conversational AI solutions; experience in R&amp;D team management is preferred.</li>
	<li>Confirmed expertise in developing RAG models, working with vector databases, prompt engineering, and fine-tuning large language models.</li>
	<li>A proven track record of successfully leading AI and Data initiatives/projects</li>
	<li>Strong programming skills in Python and proficiency with machine learning libraries such as TensorFlow, PyTorch, or JAX.</li>
	<li>Solid understanding of NLP fundamentals and experience with NLU/NLG techniques such as sentiment analysis, entity recognition, and text generation.</li>
	<li>Strong problem-solving abilities and a pragmatic approach to building scalable and robust machine learning systems.</li>
	<li>Strong communication skills with the ability to collaborate</li>
</ul>