AI Data 研发工程师（大模型数据方向）
Tasks
- Build AI data infrastructure
- Build distributed data processing platform
- Construct SFT data pipelines
- Construct preference data pipelines
- Construct pretraining data pipelines
- Design data lake and data warehouse systems
- Develop data processing SDK APIs and frameworks
- Generate captions and extract embeddings
- Implement CPU and GPU hybrid processing
- Implement RLHF and RLAIF data construction
- Implement data asset management data quality management and data governance
- Implement data versioning and metadata management
- Manage multimodal data
- Optimize data storage compute index and distribution
- Orchestrate data pipeline execution
- Perform data parsing cleaning filtering deduplication and quality evaluation
- Reduce data usage cost for model development
- Set up task scheduling monitoring logging metrics observability
Perks/Benefits
- N/A
Skills/Tech-stack
Airflow | Airflow Workflows | Arrow | Caption Generation | Clustering | Compaction | Data Lake | Data Quality | Data Quality Filtering | Data Warehouse | Data cleaning | Data pipeline | Deduplication | Distributed Systems | DolphinScheduler | Embedding | Flink | Go | Iceberg | Indexing | Java | Kubernetes | Lance | Linux | Manifest | Metadata Management | PB Scale Data | Paimon | Parquet | Partitioning | Python | Quality Filtering | RLAIF | RLHF | Ray | SFT | Spark | Vector Search | WebDataset
Education
N/A
Roles
AI | AI Engineer | Data Engineer | Engineer
Regions
Countries
States
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