Large Model Project Manager

Responsibilities

1. Based on company According to strategic needs, cooperate with technical classmates to carry out tasks such as LLM model training data sample set annotation, model iteration effect evaluation, industry application research, and safety and compliance assurance in the direction of program code, and work together with upstream product technology to jointly promote the achievement of business goals 2. Design and implement the AI training process for large language models, continuously optimize and iterate, and lead the team to efficiently complete annotation and content production projects 3. Build an AI content quality management system, be responsible for quality results, and continue to perform problem diagnosis and data analysis. , model optimization and other work 4. Responsible for managing the annotation team, actively promoting the optimization of annotation tools, organizational processes and delivery processes, and improving and improving the team's delivery capabilities 5. Assisting in the design of the product's AI model evaluation system and the output of evaluation conclusions and Able to conduct systematic analysis based on evaluation conclusions, put forward valuable improvement suggestions, and collaborate on research and development to improve model effects.

Qualifications

1. Bachelor degree or above, technical background in AI-related fields, evaluation and data analysis background, or more than 2 years of content or Applicants with work experience in policy security-related products are preferred 2. Applicants with relevant work experience in the fields of code quality testing, natural language processing, search, and artificial intelligence, and experience in AI project delivery are preferred 3. Proficient in using data analysis tools such as SQL and Python, and possess Data acquisition, classification and analysis capabilities 4. Able to accurately understand business demands, sensitive to quality/data changes, able to discover problems through a unique perspective or scientific methods, and promote the achievement of business indicators and the implementation of strategies 5. Formulate business plans and goals Management and human efficiency management work, fully communicate and collaborate with upstream and downstream teams, and pay attention to team performance data and goal achievement 6. Be proactive, have passion for AI, and have strong teamwork, organizational coordination, and complex problem-solving abilities.