Sr. Data Engineer - AI ML
Tasks
- Automate workflows for content ingestion
- Collaborate on data ingestion and retrieval strategies
- Design data pipelines for AI systems
- Design feedback loops for AI knowledge refinement
- Develop knowledge bases and vector stores
- Document data schemas and pipelines
- Enforce data governance and security standards
- Engineer RAQ/RAG pipelines
- Ensure data quality and traceability
- Evaluate new AI data technologies
- Implement monitoring and observability
Perks/Benefits
- Bonus program
- Comprehensive benefits
- Flexible work
- Inclusive environment
- Life leave
- Professional development
- Retirement options
- Vacation days
Skills/Tech-stack
AWS Glue | AWS Lambda | AWS Neptune | AWS S3 | Airflow | ArangoDB | Athena | Context chunking | Data Modeling | Dspy | ECS | Elastic Vector Search | Embedding Generation | Faiss | LLM workflows | Langchain | Llamaindex | Milvus | Model Context Protocol | Neo4j | NoSQL | Pinecone | Prefect | Prompt evaluation | Python | Redshift | Retrieval contexts | SQL | Schema Design | Semantic Kernel | Semantic indexing | Step Functions | Vector Search | Weaviate
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