AI Data Engineer (Document Intelligence & GenAI)
Tasks
- Apply data governance and security
- Build batch data pipelines
- Build embedding models
- Build streaming data pipelines
- Design document ingestion pipelines
- Develop RAG pipelines
- Develop content extraction solutions
- Evaluate emerging AI document intelligence technologies
- Implement CI/CD best practices
- Implement semantic search and vector retrieval
- Integrate data from APIs and databases
- Integrate pipelines with Azure and Databricks
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Spark | CI/CD | Data Governance | Databricks | Delta Lake | Embedding Models | Fine Tuning | Kafka | Langchain | Language Models | Large Language Models | Llamaindex | LoRA | Metadata Management | Microsoft Azure | Microsoft Fabric | Model Fine-tuning | OCR | PEFT | Prompt engineering | PySpark | Python | RAG | Retrieval-Augmented Generation | SQL | Semantic Search | Text to Speech | Vector Databases | Version control | Vision Language Models | Vision-language
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Science in Artificial Intelligence | Bachelor of Science in Computer Science | Bachelor of Science in Data Engineering
Roles
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