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Ai Rag Jobs in Michigan (NOW HIRING)

Amway

Sr AI Engineer

Ada, MI · On-site

$115K - $142K/yr

You'll work on agentic systems, retrieval-augmented generation (RAG) pipelines, and reusable AI services that power real business use cases. Depending on experience, this role may focus on owning ...

Corning

$111K - $146K/yr

Build and support chatbot, RAG, conversational AI, and model-connected application capabilities. Contribute to application development efforts that make AI agents and tools easier for users to access ...

Corning

Lead or support chatbot, RAG, conversational AI, agentic AI, and AI assistant integration initiatives. Help create user-friendly interfaces and application experiences for AI agents and tools.Apply ...

SwiftCruit

Senior Engineer, AI

Novi, MI · On-site

$90.75 - $133.10/hr

Design and implement RAG pipelines across heterogeneous enterprise datasets, including requirements ... Implement responsible AI practices including guardrails, content filtering, access controls ...

Corning

$93K - $122K/yr

What would be a plus? -Experience leading enterprise AI, GenAI, chatbot, RAG, or AI assistant initiatives. -Experience with MCP development or agentic AI solution patterns. -Experience with ...

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Ai Rag information

What are the key skills and qualifications needed to thrive as an AI researcher?

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 is an AI RAG?

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 common challenges faced by AI RAG 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 Michigan? For Ai Rag jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Michigan look for? The top searched job categories for Ai Rag jobs in Michigan are:
What cities in Michigan are hiring for Ai Rag jobs? Cities in Michigan with the most Ai Rag job openings:
Ai Rag jobs near you

AI Engineer (GenAI & RAG)

GG Tech Global

Grand Rapids, MI • On-site

Other

Posted 18 days ago

Job description

Job Title: Lead AI Engineer (GenAI & RAG)Overview / Summary

We are seeking an experienced Python Developer with 10+ years of software engineering experience, including 1+ years of experience with AI/RAG.

Key Responsibilities
  • Lead onsite and offshore development teams.
  • Help the product owner and development team achieve customer satisfaction.
  • Connect with stakeholders to understand customer requirements in detail and translate business requirements for the offshore team.
  • Remove impediments and coach the team on resolving blockers.
  • Help development teams identify and address gaps in the agile framework.
  • Resolve conflicts and issues that occur during project execution.
  • Support the product owner by providing clarifications when needed.
  • Document business meeting requirements and notes, and track and close action items.
Required Qualifications
  • 10+ years of experience in software engineering and/or data science.
  • 1+ years of experience in AI/RAG/ML development roles.
  • Strong knowledge of Retrieval-Augmented Generation (RAG).
  • Knowledge of machine learning, deep learning, and natural language processing (NLP).
  • Knowledge of Azure services.
  • Understanding of APIs, microservices, and distributed systems.
  • Knowledge of vector databases.
  • Understanding of DevOps/CI-CD pipelines for machine learning and AI.
  • Exposure to AI governance and compliance.
  • Good communication skills.

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