Retrieval Augmented Generation Rag Jobs in Pleasanton, CA

Focuses on implementing retrieval-augmented generation (RAG) pipelines, integrating LLMs with structured/unstructured data sources, and fine-tuning models for specific use cases. Key Skills:

The ideal candidate will have hands-on experience building scalable full-stack solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Vector Databases ...

We are now hiring a Sr. AI Engineer - LLM, RAG to lead the development of Retrieval-Augmented Generation (RAG) systems that harness the power of large language models (LLMs) and real-world knowledge ...

We are now hiring a Sr. AI Engineer - LLM, RAG to lead the development of Retrieval-Augmented Generation (RAG) systems that harness the power of large language models (LLMs) and real-world knowledge ...

THE ROLE Join our agile team to shape and deliver the industry's premier enterprise Retrieval-Augmented Generation (RAG) platform from the ground up. You will own end-to-end full-stack feature ...

Experience architecting and implementing Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding ...

* Join our agile team to shape and deliver the industry's premier enterprise Retrieval-Augmented Generation (RAG) platform from the ground up. You will own end-to-end full-stack feature development at ...

You will lead end-to-end engineering and research efforts spanning large-scale Retrieval-Augmented Generation (RAG), world knowledge understanding, conversational reasoning, knowledge generation and ...

Strong technical expertise in large language models (LLMs), Retrieval-Augmented Generation (RAG), NLP, and distributed systems. Demonstrated ability to define long-term technical strategy while ...

... Retrieval-Augmented Generation (RAG) - Vector databases - Prompt engineering - Large Language Models (LLMs) - Application: Send suitable profiles and contact details to rams@vensoft.com

Implement and optimize Retrieval-Augmented Generation (RAG) pipelines that combine structured and unstructured enterprise data sources. * Partner with AI engineers, platform teams, and product ...

Design and execute validation strategies for AI/ML and Retrieval-Augmented Generation (RAG) features, including model quality, grounding, and safety evaluation. Major Responsibilities or Assigned ...

... Retrieval-Augmented Generation (RAG) pipelines to power intelligent search and Q&A experiences, integrating vector search with LLM-based generation. • Design and deploy Claude-based agents and ...

Build and integrate Retrieval-Augmented Generation (RAG) solutions. * Work with Large Language Models (LLMs) and contribute to LLM-powered applications and services. * Assist with cloud architecture ...

... Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval systems. • Design ...

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 ...

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 ...

Additionally, the candidate will implement Retrieval-Augmented Generation (RAG) models and fine-tune open-source models from leading providers like Meta, Google, Deepseek, and Nvidia. Collaboration ...

You will lead end-to-end engineering and research efforts spanning large-scale Retrieval-Augmented Generation (RAG), world knowledge understanding, conversational reasoning, knowledge generation and ...

You will lead end-to-end engineering and research efforts spanning large-scale Retrieval-Augmented Generation (RAG), world knowledge understanding, conversational reasoning, knowledge generation and ...