Director, Data & AI Evaluation(J31964)

1. Build a company-level "data factory" to achieve an integrated data collection, processing, annotation and return loop between the end and the cloud. 2. Build a full-stack automated evaluation system covering basic models, industry models, and application systems. 3. Develop data quality standards and model evaluation norms, and regularly release capability rankings. 4. Develop intelligent data mining and enhancement technologies to improve the efficiency of data utilization in scarce scenarios. 5. Take the lead in building an AI compliance and ethical review mechanism to ensure that data and models are legal and compliant.

Have experience in large-scale data engineering and AI evaluation system construction, and be familiar with the data closed-loop process. 2. Proficient in technologies such as automated annotation, data cleaning, negative sample mining, and synthetic data generation. 3. Led the design of an AI model automated evaluation platform that supports multi-dimensional assessment. 4. Familiarity with mainstream evaluation benchmark construction methods is required. Candidates with experience in building their own evaluation sets are preferred. 5. Have a systematic understanding of data compliance, privacy protection and AI ethics.