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Ai Rag Jobs in California (NOW HIRING)

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

... of RAG systems that combine LLMs (e.g., LLAMA, Mistral, Claude, GPT) with structured and unstructured external information sources. • Develop AI-powered assistants to support technicians in ...

Working knowledge of generative AI, LLMs, prompting, and RAG concepts * Strong analytical, communication, and cross-functional collaboration skills Job Type & Location This is a Contract position ...

Working knowledge of generative AI, LLMs, prompting, and RAG concepts * Strong analytical, communication, and cross-functional collaboration skills Job Type & Location This is a Contract position ...

Build production-ready AI systems for document processing (PDFs, XLSX, DOCX, CSV etc.) * Develop and deploy 1-2 RAG/knowledge base systems in the first year * Create reusable GenAI frameworks and ...

We are seeking a Staff, Software Engineer with deep expertise in Generative AI , LLMs , Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This role ...

We are seeking a Staff, Software Engineer with deep expertise in Generative AI , LLMs , Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This role ...

Staff, Software Engineer

Cupertino, CA · On-site

$143K - $286K/yr

We are seeking a Staff, Software Engineer with deep expertise in Generative AI , LLMs , Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This role ...

Staff, Software Engineer

Sunnyvale, CA · On-site

$143K - $286K/yr

We are seeking a Staff, Software Engineer with deep expertise in Generative AI , LLMs , Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This role ...

We are seeking a Staff, Software Engineer with deep expertise in Generative AI , LLMs , Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This role ...

We are seeking a Staff, Software Engineer with deep expertise in Generative AI , LLMs , Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This role ...

We are seeking a Staff, Software Engineer with deep expertise in Generative AI , LLMs , Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This role ...

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Showing results 1-20

Ai Rag information

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What are AI RAGs?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are some common challenges faced by AI RAG (Retrieval-Augmented Generation) engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What are popular job titles related to Ai Rag jobs in California? For Ai Rag jobs in California, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in California look for? The top searched job categories for Ai Rag jobs in California are:
What cities in California are hiring for Ai Rag jobs? Cities in California with the most Ai Rag job openings:
Senior AI Engineer - LLM, RAG

Senior AI Engineer - LLM, RAG

BrightAI

Palo Alto, CA • On-site

$123K - $168K/yr

Full-time

Posted 6 days ago


Job description

Job Summary:
Bright.AI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation. They are seeking a Senior AI Engineer to lead the development of Retrieval-Augmented Generation systems that leverage large language models to assist technicians in troubleshooting complex industrial issues.
Responsibilities:
• Lead the architecture and development of RAG systems that combine LLMs (e.g., LLAMA, Mistral, Claude, GPT) with structured and unstructured external information sources.
• Develop AI-powered assistants to support technicians in diagnosing and resolving anomalies or failures in factory, plant, or industrial settings.
• Build pipelines to ingest, preprocess, and index large corpora of documents (manuals, logs, notes, procedures) for semantic search and grounding.
• Customize and fine-tune foundational models to incorporate domain-specific language, tone, and logic for industrial troubleshooting scenarios.
• Collaborate with product, data, and cloud teams to design scalable, privacy-compliant, and latency-sensitive LLM applications.
• Design evaluation strategies to measure performance, accuracy, and user experience of RAG-enabled systems in production settings.
• Stay up to date with the latest advances in LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques into the product roadmap.
Qualifications:
Required:
• M.S. or Ph.D. in Computer Science, AI, Machine Learning, or a related field, with specialization in NLP or deep learning.
• Strong research or applied background in large language models (LLMs) and retrieval-augmented generation (RAG) systems.
• 5+ years of experience in machine learning or AI with a strong focus on NLP, LLMs, or conversational AI.
• Fluency with modern LLMs and open-source foundational models (e.g., LLAMA, Falcon, Mistral, GPT, Claude).
• Experience building RAG pipelines with tools like LangChain, LlamaIndex, or custom vector database integrations, with at least one production grade system was built.
• Fluency with prompt engineering, instruction tuning, or fine-tuning open-source models.
• Deep understanding of document retrieval (semantic search, embedding generation, similarity metrics) and vector stores (e.g., FAISS, Weaviate, Pinecone).
• Strong foundation in core machine learning techniques, including experience with reinforcement learning (RL) or decision-making models.
• Proficiency with ML development frameworks such as PyTorch, Hugging Face Transformers, or similar.
• Strong Python programming is a must.
• Experience integrating AI systems into real-world applications with user-facing interfaces and operational constraints.
• Excellent problem-solving and critical thinking skills; ability to design solutions for complex, ambiguous problems.
• Strong written and verbal communication skills, with ability to collaborate cross-functionally with engineers, product managers, and domain experts.
Preferred:
• Experience applying LLMs in industrial or physical infrastructure settings (e.g., manufacturing, logistics, utilities, energy).
• Knowledge of industrial control systems, maintenance workflows, or technician support processes.
• Exposure to multimodal models or integrating textual data with sensor and/or time-series data.
• Prior experience in a startup or a fast-paced environment building LLM-powered products from the ground up.
Company:
BrightAI provides physical AI solutions for infrastructure and services. Founded in 2020, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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About BrightAI

Sourced by ZipRecruiter

Industry

Software development

Company size

11 - 50 Employees

Headquarters location

San Francisco, CA, US

Year founded

2019