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aws sql python databricks spark
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📋 Description

  • Own architecture and delivery of production-grade LLM and ML solutions.
  • Design and optimize RAG pipelines: retrieval, chunking, indexing.
  • Build scalable LLM services and agentic workflows with ML systems.
  • Optimize architecture trade-offs: latency, cost, scalability, reliability.
  • Architect distributed GenAI/ML on Databricks (Spark, MLflow).
  • Produce evaluation frameworks for quality, hallucination, performance.
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