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Temporary Retrieval Augmented Generation Jobs in Ohio

Implement retrieval-augmented generation (RAG) strategies to enhance the context and relevance of generated outputs. * Manage and optimize vector databases for efficient storage and retrieval of data ...

Data Engineer

Cincinnati, OH · On-site

$109.90K - $132K/yr

Develop and maintain data pipelines specifically tailored for Retrieval-Augmented Generation (RAG) type Large Language Model (LLM) workflows. * Ensure efficient data retrieval and augmentation ...

AI Architect

Westerville, OH

$60.75 - $80/hr

Experience in Generative AI architectures and frameworks such as retrieval augmented generation ... Individuals with temporary visas such as E, F-1, H-1, H-2, L, B, J, or TN or who need sponsorship ...

AI Architect

Westerville, OH · On-site

$60.75 - $80/hr

Experience in Generative AI architectures and frameworks such as retrieval augmented generation ... Individuals with temporary visas such as E, F-1, H-1, H-2, L, B, J, or TN or who need sponsorship ...

Data Engineer- Full Stack

Mason, OH · On-site +1

$107.70K - $129.30K/yr

You will design and integrate Gen AI capabilities - including LLM-powered data enrichment, retrieval-augmented generation (RAG), and intelligent automation - into the data platform. You will lead the ...

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Temporary Retrieval Augmented Generation information

What is the difference between Temporary Retrieval Augmented Generation vs Data Scientist?

AspectTemporary Retrieval Augmented GenerationData Scientist
Required CredentialsTypically requires knowledge of AI, NLP, and some programming skillsRequires degrees in data science, statistics, or related fields, often with certifications in data analysis
Work EnvironmentOften project-based, working with AI models and large datasets in tech or research firmsUsually in corporate, research, or tech companies analyzing data to inform decisions
Industry UsageUsed in AI development, natural language processing, and machine learning projectsApplied across industries for data analysis, predictive modeling, and business insights

Temporary Retrieval Augmented Generation focuses on enhancing AI models with retrieval techniques, while Data Scientists analyze data to generate insights. Both roles require technical skills but serve different purposes within the tech and data ecosystem.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Ohio? The most popular types of Retrieval Augmented Generation jobs in Ohio are:
What are popular job titles related to Temporary Retrieval Augmented Generation jobs in Ohio? For Temporary Retrieval Augmented Generation jobs in Ohio, the most frequently searched job titles are:
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AI Engineer

Other

Posted 16 days ago


Job description

Responsibilities:

  • Develop, test, and deploy advanced AI/ML models and algorithms using Python.Design and implement prompt engineering techniques to optimize model responses and performance.
  • Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
  • Utilize AI agentic frameworks to create intelligent systems capable of autonomous decision-making.
  • Work with large language models (LLMs) to develop applications that understand and generate human-like text.
  • Implement retrieval-augmented generation (RAG) strategies to enhance the context and relevance of generated outputs.
  • Manage and optimize vector databases for efficient storage and retrieval of data used in AI applications.
  • Conduct research and stay up to date with the latest advancements in AI/ML technologies and methodologies.
  • Document processes, models, and methodologies for future reference and knowledge sharing.

Requirements:

  • Bachelor s or master s degree in computer science, Artificial Intelligence, Machine Learning, or a related field.
  • Proven experience in advanced Python programming, with a strong understanding of data structures and algorithms.
  • Demonstrated expertise in prompt engineering and its application within AI models.
  • Familiarity with AI agentic frameworks and their implementation in real-world applications.
  • Experience working with large language models (LLMs) and understanding their architecture and functionalities.
  • Knowledge of retrieval-augmented generation (RAG) techniques and vector databases.
  • Ability to work effectively in a collaborative environment and communicate complex concepts to non-technical stakeholders.
  • Strong analytical and problem-solving skills with a focus on delivering high-quality results.

Desired Skills:

  • Experience with frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face.
  • Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their AI/ML services.
  • Knowledge of data preprocessing and data engineering practices.