Retrieval Augmented Generation Rag Jobs in Pennsylvania

Develop Retrieval-Augmented Generation (RAG) solutions using vector databases and Large Language Models (LLMs). * Deploy, monitor, and manage ML models using AWS SageMaker and MLOps best practices.

Basic understanding of Retrieval-Augmented Generation (RAG) and vector databases. * Comfortable working with LLM APIs and integrating them into applications. * A solid understanding of machine ...

Strong understanding of prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques such as LoRA. * Experience with AI application development, preferably integrating APIs or ...

... Retrieval-Augmented Generation (RAG) pipelines using open-source vector databases (Qdrant, Chroma, Milvus, pgvector) - Engineer Python-based solutions for LLM inference, prompt design, and system ...

Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate) * Build custom applications with LLM frameworks such as LangChain, DSPy * Deploy ...

Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate) * Build custom applications with LLM frameworks such as LangChain, DSPy * Deploy ...

Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate) * Build custom applications with LLM frameworks such as LangChain, DSPy * Deploy ...

Design and implement retrieval-augmented generation (RAG) systems and semantic search architectures * Build production-grade LLM applications and agentic systems * Deploy scalable AI solutions across ...

Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate) * Build custom applications with LLM frameworks such as LangChain, DSPy * Deploy ...

Design and implement retrieval-augmented generation (RAG) systems and semantic search architectures * Build production-grade LLM applications and agentic systems * Deploy scalable AI solutions across ...

Design and implement retrieval-augmented generation (RAG) systems and semantic search architectures * Build production-grade LLM applications and agentic systems * Deploy scalable AI solutions across ...

Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate) * Build custom applications with LLM frameworks such as LangChain, DSPy * Deploy ...

Design and implement retrieval-augmented generation (RAG) systems and semantic search architectures * Build production-grade LLM applications and agentic systems * Deploy scalable AI solutions across ...

Design and implement retrieval-augmented generation (RAG) systems and semantic search architectures * Build production-grade LLM applications and agentic systems * Deploy scalable AI solutions across ...

Develop and integrate Retrieval-Augmented Generation (RAG) pipelines, including ingestion, chunking, embeddings, vector and hybrid retrieval, reranking, contextual compression, and grounding ...

... retrieval-augmented generation (RAG), or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor

... retrieval-augmented generation (RAG), or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor

... retrieval-augmented generation (RAG) and prompt engineering. • Collaborate with cross-functional teams to integrate AI capabilities into internal tools, workflows, and digital products. • ...

Develop retrieval-augmented generation (RAG) systems that connect AI models with trusted scientific and scholarly content. * Create intelligent capabilities for search, ranking, recommendation ...

Develop retrieval-augmented generation (RAG) systems that connect AI models with trusted scientific and scholarly content. * Create intelligent capabilities for search, ranking, recommendation ...