算法工程师-大模型数据方向
Tasks
- Build annotation support tools to improve throughput
- Build end to end model data pipeline
- Build golden corpus using clustering and scoring
- Close loop using model feedback to iterate datasets
- Construct data quality evaluation metrics
- Create multidimensional labeling system
- Define corpus classification standards
- Design model knowledge framework
- Develop AI assisted annotation workflow
- Develop data governance framework
- Implement corpus cleaning scripts
- Map knowledge graph features
- Perform noise removal deduplication and desensitization
- Set source specific quality standards
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Spark | Clustering | Data Annotation | Data Annotation Automation | Data Governance | Data Quality | Data Quality Evaluation | Data cleaning | Data labeling | Fine Tuning | Knowledge graphs | Language Processing | Natural Language | Natural Language Processing | Pandas | Pretraining | PyTorch | Python | Quality evaluation | Regular Expressions | TensorFlow | Transformer
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
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