Retrieval Augmented Generation Rag Jobs in California

Build Retrieval-Augmented Generation (RAG) solutions using enterprise data. * Develop prompt engineering strategies and context management pipelines. * Fine-tune and optimize LLM-powered applications ...

Expertise in building Retrieval-Augmented Generation (RAG) pipelines * Knowledge of semantic layers and knowledge graphs for structured reasoning * Proficient in Python and FastAPI for backend and ...

... retrieval-augmented generation (RAG) * 7+ Years Exp - coding experience in Python, with proficiency in ML/NLP libraries * 7+ Years Exp - healthcare data standards like FHIR, HL7, ICD/CPT, X12 EDI ...

Contribute to architecture, retrieval-augmented generation (RAG) design, prompt engineering, and CI/CD practices that support rapid, reliable delivery of AI features. Succeed in this role by shipping ...

Guided teams on LLM usage patterns, including prompt design, grounding strategies, and Retrieval-Augmented Generation (RAG) * Collaborated with AI architects and MLOps teams to ensure Responsible AI ...

AI/ML & Generative AI(Primary Skill set) NLP and Transformer Architectures Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Model Context Protocol (MCP) Frameworks ...

Retrieval-augmented generation (RAG) systems for dynamic hotel and travel searches * Preference engines that learn and evolve from member interactions * Lightweight AI orchestration layers integrated ...

Architect and implement Retrieval-Augmented Generation (RAG) systems for document Q&A, enabling business teams to query fund documents, investor letters, and market research. * Design, deploy, and ...

Develop tools for training and fine-tuning large language models, advanced Retrieval-Augmented Generation (RAG) pipelines, vector databases and agentic frameworks. * Build efficient data pipelines to ...

Build and scale Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestrations, and API integrations connecting LLMs to internal databases and enterprise software. * Evaluations ...

The ideal candidate should have hands-on expertise with Retrieval-Augmented Generation (RAG), Agentic AI workflows, and LLM-based automation, with the ability to integrate AI systems into complex ...

The ideal candidate should have hands-on expertise with Retrieval-Augmented Generation (RAG), Agentic AI workflows, and LLM-based automation, with the ability to integrate AI systems into complex ...

Develop tools for training and fine-tuning large language models, advanced Retrieval-Augmented Generation (RAG) pipelines, vector databases and agentic frameworks. * Build efficient data pipelines to ...

Implement Retrieval-Augmented Generation (RAG) and orchestrate AI agents using tools like LangChain, LangGraph, or CrewAI. * Integrate Large Language Models (LLMs) with enterprise vector databases ...

Preferred Qualifications Strong background and experience in Machine Learning, NLP, and RAG. Strong ... D. in Computer Science, Machine Learning, information retrieval, data mining, or a related field 8+ ...

We are hiring an AI Engineer specializing in LLMs (Large Language Models), Retrieval Augmented Generation ( RAG ), and Generative AI. The role involves building advanced AI solutions that leverage ...

Preferred Qualifications Strong background and experience in Machine Learning, NLP, and RAG. Strong ... D. in Computer Science, Machine Learning, information retrieval, data mining, or a related field 8+ ...

AI-Powered Knowledge Systems & Retrieval-Augmented Generation (RAG) * Architect and implement RAG platforms and AI-ready knowledge repositories. * Design intelligent retrieval systems using hybrid ...

... retrieval-augmented generation (RAG) systems. • Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems. • Help shape the future of AI ...

Familiarity with vector databases (e.g., FAISS, Milvus, Pinecone) and retrieval augmented generation (RAG). * Experience deploying AI models to production environments. * Strong understanding of data ...