Retrieval Augmented Generation Rag Jobs in Boston, MA

Experience designing Retrieval-Augmented Generation (RAG) pipelines and working with vector databases. * Strong understanding of prompt engineering, embeddings, model evaluation, and AI application ...

You will contribute to real-world AI initiatives, leveraging technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based architectures to address business ...

You will contribute to real-world AI initiatives, leveraging technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based architectures to address business ...

... Retrieval-Augmented Generation (RAG) pipelines and agentic frameworks • Champion software engineering best practices: clean code, robust testing, code reviews, and clear documentation • Stay ...

... Retrieval-Augmented Generation (RAG) pipelines and agentic frameworks • Champion software engineering best practices: clean code, robust testing, code reviews, and clear documentation • Stay ...

The role translates complex legal and operational needs into testableprototypes and proof-of-concept solutions--including generative AI applications,retrieval-augmented generation (RAG) solutions ...

Key initiatives include intelligent research tools, retrieval-augmented generation systems, large language model applications, and production-ready autonomous workflows. You will also help set ...

... Retrieval-Augmented Generation (RAG), agentic AI, and large language model (LLM) integration. This role is ideal for someone who thrives in bridging software engineering and applied AI-turning ...

... retrieval-augmented generation (RAG). • Experience driving coordinated action between cross-functional teams (product, research, stakeholders) working from different locations around the world. • ...

You'll work on distributed systems that combine traditional infrastructure automation with large language models (LLMs), retrieval-augmented generation (RAG), and intelligent agents. What You'll Do

Leverage Retrieval-Augmented Generation (RAG), fine-tuning, and traditional ML techniques to develop hybrid AI models that address engineering challenges. * Continuous Improvement: Identify and ...

Preferred : • Experience applying large language models (LLMs) for retrieval-augmented generation (RAG) for technical problems. • Proficiency in Python, C/C++, Java, or similar. • United States ...

Retrieval-Augmented Generation (RAG) * ASR frameworks: OpenAI Whisper, Meta Wave2Vec-BERT * Hugging Face exporters and Swift-based transformer tooling * Accent-adaptive tuning and speech ...

Familiarity with Retrieval-Augmented Generation (RAG) patterns, embedding models, vector databases, and semantic search techniques to ground AI outputs in enterprise content. Experience working with ...

You will design data products, orchestrate multi-agent workflows, develop Retrieval-Augmented Generation (RAG) systems, integrate enterprise knowledge sources, and establish the governance and ...

Deep understanding of the AI Agent paradigm, including hands-on experience with LLMs, prompt engineering, agentic loop design, and retrieval-augmented generation (RAG). * Experience driving ...

You will design data products, orchestrate multi-agent workflows, develop Retrieval-Augmented Generation (RAG) systems, integrate enterprise knowledge sources, and establish the governance and ...

Familiarity with Retrieval-Augmented Generation (RAG) and connecting LLMs to enterprise documents, databases, knowledge repositories, or other internal data sources * Familiarity with Agentic AI ...

Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. * Build multimodal AI workflows ...

... language models, retrieval-augmented generation, and software-testing methods to generate ... LLM/RAG test-generation pipeline. Design, implement, and iterate prompts, retrieval workflows ...