Senior Data Scientist
Cleveland, OH · On-site
Design and implement Retrieval-Augmented Generation (RAG) pipelines * Develop solutions for semantic search, document intelligence, and enterprise search capabilities * Optimize prompt engineering ...
Senior Data Scientist
Cleveland, OH · On-site
Design and implement Retrieval-Augmented Generation (RAG) pipelines * Develop solutions for semantic search, document intelligence, and enterprise search capabilities * Optimize prompt engineering ...
Senior Data Scientist
Cleveland, OH · On-site
The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers ...
Senior Data Scientist
Cleveland, OH · On-site
The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers ...
The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers ...
The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers ...
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers ...
Quick apply
The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
Cloud Solutions Architect (Remote)
Akron, OH · On-site +1
$110K - $148K/yr
Lead the design of Retrieval-Augmented Generation (RAG) solutions by integrating enterprise knowledge sources, databases, APIs, and retail systems. * Evaluate emerging AI technologies and recommend ...
Cloud Solutions Architect (Remote)
Akron, OH · On-site +1
$110K - $148K/yr
Lead the design of Retrieval-Augmented Generation (RAG) solutions by integrating enterprise knowledge sources, databases, APIs, and retail systems. * Evaluate emerging AI technologies and recommend ...
Cloud Solutions Architect (Remote)
Akron, OH · Remote
$110K - $148K/yr
Lead the design of Retrieval-Augmented Generation (RAG) solutions by integrating enterprise knowledge sources, databases, APIs, and retail systems. * Evaluate emerging AI technologies and recommend ...
Cloud Solutions Architect (Remote)
Akron, OH · Remote
$110K - $148K/yr
Lead the design of Retrieval-Augmented Generation (RAG) solutions by integrating enterprise knowledge sources, databases, APIs, and retail systems. * Evaluate emerging AI technologies and recommend ...
Architect and implement multi-agent and agentic AI frameworks that support enterprise cybersecurity use cases, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings ...
Architect and implement multi-agent and agentic AI frameworks that support enterprise cybersecurity use cases, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings ...
Experience building Retrieval-Augmented Generation (RAG), vector database integrations, tool calling, function calling, and LLM-based applications. * Ability to independently own user stories from ...
Experience building Retrieval-Augmented Generation (RAG), vector database integrations, tool calling, function calling, and LLM-based applications. * Ability to independently own user stories from ...
AI Architect
$60.75 - $80/hr
Architect Generative AI solutions using the latest techniques such as retrieval augmented generation, transformer architectures, etc. to accommodate large-scale and intricate Generative AI solutions.
AI Architect
$60.75 - $80/hr
Architect Generative AI solutions using the latest techniques such as retrieval augmented generation, transformer architectures, etc. to accommodate large-scale and intricate Generative AI solutions.
AI Architect
Westerville, OH · On-site
$60.75 - $80/hr
Architect Generative AI solutions using the latest techniques such as retrieval augmented generation, transformer architectures, etc. to accommodate large-scale and intricate Generative AI solutions.
AI Architect
Westerville, OH · On-site
$60.75 - $80/hr
Architect Generative AI solutions using the latest techniques such as retrieval augmented generation, transformer architectures, etc. to accommodate large-scale and intricate Generative AI solutions.
Retrieval Augmented Generation information
What is a retrieval augmented generation?
A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.
What does a retrieval augmented generation engineer do?
A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.
What skills and qualifications are needed for retrieval augmented generation?
To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.
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 Retrieval Augmented Generation jobs in Ohio?
For Retrieval Augmented Generation jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Retrieval Augmented Generation jobs in Ohio look for?
The top searched job categories for Retrieval Augmented Generation jobs in Ohio are:
What cities in Ohio are hiring for Retrieval Augmented Generation jobs?
Cities in Ohio with the most Retrieval Augmented Generation job openings:
Senior Data Scientist
Cleveland, OH • On-site
Flexjet LLC
• Aerospace Product and Parts Manufacturing • 501 - 1,000 employees501 - 1,000 employees
Other
Re-posted 10 days ago
Flexjet rating
7.8
Based on 25 frontline employees who took The Breakroom Quiz
Job description
Overview
#J-18808-LjbffrFlexjet is seeking a Senior-Level Enterprise AI Data Scientist to design, develop, and deploy enterprise-scale AI and Generative AI solutions that improve productivity, automate workflows, and enhance decision-making across the organization. This role focuses on building LLM-powered enterprise applications, such as internal knowledge assistants, document processing systems, and workflow automation tools. The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers, software engineers, product teams, and business stakeholders to build secure, scalable, and production-ready AI solutions that align with enterprise governance and compliance standards.
Duties & Responsibilities- Design and implement enterprise-scale machine learning models, including predictive and classification systems
- Develop intelligent automation solutions to streamline business workflows
- Build and deploy LLM-powered applications, such as enterprise knowledge assistants and chatbots
- Design and implement Retrieval-Augmented Generation (RAG) pipelines
- Develop solutions for semantic search, document intelligence, and enterprise search capabilities
- Optimize prompt engineering workflows and fine-tune models using domain-specific data
- Evaluate and benchmark machine learning and LLM model performance
- Work with large-scale structured and unstructured data sources across enterprise systems
- Design and build scalable data pipelines to support AI and machine learning workflows
- Integrate AI solutions with internal systems, APIs, and enterprise platforms
- Partner with data engineering teams to design and optimize data architectures
- Deploy AI/ML models into production environments
- Implement model monitoring, performance tracking, and alerting
- Maintain model versioning, reproducibility, and lifecycle management
- Support and contribute to CI/CD pipelines for AI and ML deployments
- Ensure scalability, reliability, and performance of systems in production environments
- Implement responsible AI practices, including fairness, transparency, and risk mitigation
- Ensure compliance with enterprise data governance, privacy, and security standards
- Support model explainability and documentation requirements
- Maintain thorough documentation of models, systems, and workflows
- Translate business needs into actionable technical solutions
- Work closely with product, engineering, and analytics teams to deliver AI-driven solutions
- Communicate technical concepts and solutions clearly to non-technical stakeholders
- Contribute to system architecture decisions and design discussions
- Document workflows, design decisions, and results
- Bachelor\'s or master\'s degree in computer science, Information Technology, Data Science, or a related field, or an equivalent combination of education, training, and relevant professional experience.
- 5+ years of experience in Data Science, Machine Learning, and AI software engineering, machine learning engineering, platform engineering, MLOps, or DevOps.
- Experience building and deploying production ML systems
- Hands-on expertise in data preprocessing, feature engineering, and model evaluation
- Experience working with APIs, large datasets, and enterprise systems
- Programming: Strong proficiency in Python and SQL
- Experience developing and deploying models (regression, classification, clustering, ensembles, neural networks)
- Strong understanding of data preprocessing, feature engineering, and model evaluation
- Prompt engineering and optimization
- Retrieval-Augmented Generation (RAG)
- Embeddings and vector search
- Model evaluation and fine-tuning
- Experience working with large, complex datasets
- Data pipelines, ETL processes, and enterprise data warehouses
- API integrations and distributed/enterprise-scale systems
- Building and maintaining production-ready ML systems
- Familiarity with Docker, Kubernetes, and REST APIs
- CI/CD pipelines and version control (Git)
- Experience with AWS, Azure, or Google Cloud
- Experience developing LLM-powered applications in enterprise environments
- Hands-on experience with RAG pipelines, embeddings, and vector databases
- Strong understanding of prompt engineering and LLM evaluation techniques
- Familiarity with frameworks such as LangChain, LlamaIndex, and Hugging Face
- Knowledge of MLOps practices, including CI/CD, model monitoring, and lifecycle management
- Experience with Docker, Kubernetes, and containerized deployments
- Understanding of data governance, responsible AI, and model explainability
About Flexjet
Sourced by ZipRecruiter
Industry
Aerospace product and parts manufacturing
Company size
501 - 1,000 Employees
Headquarters location
Cleveland, OH, US
Year founded
1995