65571_Research Scientist – Large Language Models (LLMs) (Hsinchu)
台灣康寧顯示玻璃股份有限公司
本網頁由成功大學生涯發展組與104人力銀行共同經營創建，源於南區就業博覽會徵才企業職缺，同意在此提供更多且適職的工作機會予求職者
台灣康寧顯示玻璃股份有限公司
康寧是一家有著超過170年歷史的百年企業。從愛迪生燈泡的玻璃外殼到高科技顯示基板，我們在玻璃、陶瓷和光學物理領域不斷突破，為大家帶來更好的生活體驗。現在，我們的產品涵蓋光學通訊、消費性行動電子、顯示科技、車用和生命科學等多個領域。 在台灣，康寧的布局非常全面，不僅在台中和台南設有兩座玻璃基板工廠，也在新竹工研院設立了研發中心，以及內湖設立了亞洲玻璃技術中心。我們從基礎研發到生產製造，全方位支持台灣的科技產業，充分展現了我們對台灣的承諾。 康寧，我們無所不在！ We shatter impossible. People at Corning break through limitations and expectations - not once in a career, but every day - helping push our company, and the world, forward.
工作內容
Scope of Position: We are looking for talented professionals to join us in advancing AI solutions. Our team is composed of passionate professionals in the AI field who thrive on solving complex problems and dedicated to developing cutting-edge technologies that transform industries and improve daily operations. The ideal candidate will have a strong background in LLM and Natural Language Processing (NLP), and will be providing technical leadership for designing, developing, and optimizing LLMs to enhance our AI-driven products and services. Day to Day Responsibilities: • Propose and lead research activities involving LLMs customization and optimization for different applications across Corning businesses. • Design and implement LLMs using advanced RAG techniques such as Query Transformation, Index Retrieval, Re-Rank, etc. to ensure the application is precisely adapted and optimized for specific requirements. • Develop LLM agents using LangGraph framework proficient in task planning and execution, ensuring smooth integration with external tools, databases, and APIs to tackle complex problems and improve decision-making. • Develop and implement NLP models and algorithms to solve various language-related problems.
條件要求
英文 -- 聽 /精通、說 /精通、讀 /精通、寫 /精通
Minimum Qualifications: • Proven hands-on experience in developing and deploying LLMs, especially the experience with Prompt Engineering and RAG to enhance the response capabilities of LLM. • Familiar with LangChain architecture, connecting external tools, databases, and APIs. • Deep understanding of NLP techniques, including transformers, attention mechanisms, and transfer learning. • Proficiency in text data processing such as information retrieval, information extraction, text classification, feature engineering. • Strong programming skills in Python and familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Hugging Face. • Master's degree in Computer Science, Engineering or similar field of study. • Proficiency in English, both written and spoken, is required. Preferred Qualifications: • Publication record at top AI/ML venues. • Familiarity with the training and fine-tuning processes of multimodal LLMs and Encoders. • Familiarity with reinforcement learning and other advanced machine learning techniques. • Contributions to open-source projects or research publications in relevant fields. • Experience going beyond a research paper, taking ideas from experiments, to prototypes, to interactive demonstrations. • Ph. D. in related field.
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康寧台中廠
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