蚂蚁集团大模型数据智能算法工程师招聘（可内推）

Core Viewpoint - The article discusses the responsibilities and requirements for a position focused on developing advanced algorithms for large model data production, emphasizing the importance of data knowledge systems, automatic classification, authoritative evaluation sets, quality assessment, and innovative solutions in the field of artificial intelligence and deep learning [1][2][3]. Group 1: Responsibilities - The role involves designing and developing algorithms to address key issues in large model data production, including data knowledge system generation, automatic corpus classification, authoritative evaluation set construction, and quality assessment of training data [1][5]. - Specific tasks include researching automatic knowledge graph generation based on LLM, developing classification algorithms, and creating standardized evaluation sets to assess model performance [1][5]. - The position also requires establishing a data-driven system for quality assessment, identifying low-quality data, and synthesizing training data to improve model performance [1][5]. Group 2: Requirements - Candidates should possess a master's degree or higher in computer science, artificial intelligence, deep learning, or related fields, and be proficient in deep learning frameworks such as PyTorch and TensorFlow [2][6]. - Strong problem-solving skills, self-motivation, and the ability to analyze and address issues are essential, along with effective communication and coordination abilities [2][6]. - Preference is given to candidates with practical experience in large model data system design, corpus classification, evaluation set construction, and data annotation algorithms [3][4][6].