Product Manager, Retrieval-Augmented Generation and Embeddings At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited ...
Product Manager, Retrieval-Augmented Generation and Embeddings At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited ...
Senior Agentic AI Builder
San Jose, CA · On-site
$107K - $136K/yr
... 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 ...
Senior Agentic AI Builder
San Jose, CA · On-site
$107K - $136K/yr
... 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 ...
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:
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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:
Software Engineer (Java + GenAI)
San Jose, CA · On-site
$60.75 - $83.25/hr
... Retrieval-Augmented Generation (RAG) - Vector databases - Prompt engineering - Large Language Models (LLMs) - Application: Send suitable profiles and contact details to rams@vensoft.com
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Software Engineer (Java + GenAI)
San Jose, CA · On-site
$60.75 - $83.25/hr
... Retrieval-Augmented Generation (RAG) - Vector databases - Prompt engineering - Large Language Models (LLMs) - Application: Send suitable profiles and contact details to rams@vensoft.com
Python Full Stack AI
San Jose, CA · On-site
Develop Retrieval-Augmented Generation (RAG) solutions using vector databases. Integrate LLMs such as GPT, Claude, Gemini, or Llama into enterprise applications. Fine-tune, evaluate, and optimize ...
Python Full Stack AI
San Jose, CA · On-site
Develop Retrieval-Augmented Generation (RAG) solutions using vector databases. Integrate LLMs such as GPT, Claude, Gemini, or Llama into enterprise applications. Fine-tune, evaluate, and optimize ...
Agentic AI Developer (Python & AI)
Sunnyvale, CA · On-site
$60 - $82.50/hr
... Retrieval-Augmented Generation) architecture * - Hands-on experience on designing solutions using agentic frameworks like LangChain, CrewAI, Semantic Kernel and AutoGen. * - Having experience in ...
Agentic AI Developer (Python & AI)
Sunnyvale, CA · On-site
$60 - $82.50/hr
... Retrieval-Augmented Generation) architecture * - Hands-on experience on designing solutions using agentic frameworks like LangChain, CrewAI, Semantic Kernel and AutoGen. * - Having experience in ...
AI Engineer
Cupertino, CA · On-site
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 ...
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AI Engineer
Cupertino, CA · On-site
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 ...
Familiarity with Large Language Models (LLMs) and Generative AI (GenAI) technologies including Retrieval-Augmented Generation (RAG) and model tuning. * Familiarity with SLMs: model design and fine ...
Familiarity with Large Language Models (LLMs) and Generative AI (GenAI) technologies including Retrieval-Augmented Generation (RAG) and model tuning. * Familiarity with SLMs: model design and fine ...
Research Engineer
San Francisco, CA · On-site
Research and experiment with novel techniques, including reinforcement learning, retrieval-augmented generation, and autonomous reasoning * Work in a collaborative, high-impact team, translating ...
Research Engineer
San Francisco, CA · On-site
Research and experiment with novel techniques, including reinforcement learning, retrieval-augmented generation, and autonomous reasoning * Work in a collaborative, high-impact team, translating ...
This is an AI-native software engineering role: you will spend your time building multi-agent orchestration systems, retrieval-augmented generation pipelines, tool-use frameworks, and knowledge graph ...
This is an AI-native software engineering role: you will spend your time building multi-agent orchestration systems, retrieval-augmented generation pipelines, tool-use frameworks, and knowledge graph ...
Staff Software Developer 2
San Diego, CA · On-site +1
Support implementation of retrieval-augmented generation workflows, including document chunking, metadata handling, vector embeddings, semantic search, and citation-enabled response generation.
Staff Software Developer 2
San Diego, CA · On-site +1
Support implementation of retrieval-augmented generation workflows, including document chunking, metadata handling, vector embeddings, semantic search, and citation-enabled response generation.
... 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 ...
... 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 ...
Staff Software Developer 2
San Diego, CA · On-site +1
Support implementation of retrieval-augmented generation workflows, including document chunking, metadata handling, vector embeddings, semantic search, and citation-enabled response generation.
Staff Software Developer 2
San Diego, CA · On-site +1
Support implementation of retrieval-augmented generation workflows, including document chunking, metadata handling, vector embeddings, semantic search, and citation-enabled response generation.
Staff Software Developer 2
San Diego, CA · On-site +1
Support implementation of retrieval-augmented generation workflows, including document chunking, metadata handling, vector embeddings, semantic search, and citation-enabled response generation.
Staff Software Developer 2
San Diego, CA · On-site +1
Support implementation of retrieval-augmented generation workflows, including document chunking, metadata handling, vector embeddings, semantic search, and citation-enabled response generation.
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 ...
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 ...
AI/ML Engineer
Woodland Hills, CA · On-site
$70K - $75K/yr
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 ...
AI/ML Engineer
Woodland Hills, CA · On-site
$70K - $75K/yr
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 ...
Develop and fine-tune retrieval-augmented generation (RAG) systems over scientific literature corpora for real-time knowledge synthesis * Collaborate with materials scientists, computational chemists ...
Develop and fine-tune retrieval-augmented generation (RAG) systems over scientific literature corpora for real-time knowledge synthesis * Collaborate with materials scientists, computational chemists ...
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 ...
Quick apply
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 ...
AIML engineer
San Francisco, CA · On-site
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 ...
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AIML engineer
San Francisco, CA · On-site
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 ...
AI/ML Engineer
Santa Clara, CA · On-site
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 ...
Quick apply
AI/ML Engineer
Santa Clara, CA · On-site
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 ...
Entrylevel Retrieval Augmented Generation information
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Google rating
8.9
Based on 102 frontline employees who took The Breakroom Quiz
40th of 242 rated software companies
Job description
At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day. In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development. One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
Large Language Models (LLMs) need access to fresh, specialized data to give users helpful responses. Doing this at scale while keeping things flexible enough to let developers try new ideas quickly involves bridging the gaps between many infrastructure capabilities: chunking, inference, embeddings retrieval, and more. You will work with stakeholders across the Context and Understanding organization to make sure Google's AI powered experiences can leverage the Retrieval-Augmented Generation (RAG) setups to optimize cost, quality, and latency. Behind the scenes, RAG systems rely on vector (embeddings) search as a critical technology to enable fast, cheap, semantic queries. You will also work with the broader AI Foundations organization to guide the evolution of our embeddings capabilities across a number of storage and serving systems.
The Core team builds the technical foundation behind Google's flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google's products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits.
Responsibilities:
- Partner with research teams across DeepMind, Research, and Core to advance the next-generation RAG technologies at Google, and make them available across the company.
- Partner with clients to unlock new business opportunities by resolving critical bottlenecks in Google's RAG technologies.
- Drive the horizontal product outlook and road map to ensure smooth and efficient journeys across multiple products in the AI Foundations portfolio.
- Conduct client and external research to surface top client pain points and emerging opportunities.
- Define and track success metrics for user value and developer velocity.
About Google
Sourced by ZipRecruiter
Industry
Software development and technology, communication and media
Company size
10,000+ Employees
Headquarters location
Mountain View, CA, US