Internship Retrieval Augmented Generation Jobs in California

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 ...

Implement conversation memory, tool calling, function execution, and retrieval-augmented generation (RAG) workflows. * Collaborate with product managers, AI engineers, and software developers to ...

Implement and optimize Retrieval-Augmented Generation (RAG) pipelines for enhanced information retrieval and generation. * Design and implement efficient vector-based search solutions for semantic ...

... 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 ...

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 ...

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

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 ...

While most internships touch one or two of these domains, AVEVA brings them together within a ... Familiarity with concepts such as prompt engineering, Retrieval-Augmented Generation (RAG ...

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 pipelines for context-aware AI applications • MCP (Model Context Protocol) - Practical experience with MCP client/server patterns for structured tool-to-data ...

Retrieval-Augmented Generation (RAG) architectures * Vector database experience * Semiconductor or manufacturing domain knowledge

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:

Build and deploy RAG (Retrieval-Augmented Generation) pipelines * Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications * Develop and orchestrate agentic AI workflows with ...

This role focuses on building scalable systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI workflows . The ideal candidate will bring deep expertise ...

Experience building retrieval-augmented generation, vector search, embedding retrieval, or semantic search systems. Experience working with transformer architectures such as BERT, T5, Llama, Gemma ...

Advanced AI/ML: Strong expertise in Large Language Models (LLMs), including techniques like prompt engineering and Retrieval-Augmented Generation (RAG) * Coding Excellence: Proficiency in ...

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

... RAG (Retrieval-Augmented Generation) techniques. • Strong understanding of natural language processing (NLP). Experience with data preprocessing and model fine-tuning. • Familiarity with ...

Implement conversation memory, tool calling, function execution, and retrieval-augmented generation (RAG) workflows. * Collaborate with product managers, AI engineers, and software developers to ...

Define reusable engineering patterns for prompt frameworks, retrieval-augmented generation, text-to-SQL, semantic data models, agent workflows, evaluation, guardrails, human review, and workflow ...