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Generative Ai Testing Jobs in Ohio (NOW HIRING)

NEURA Robotics

$100 - $130/hr

Strong methodological expertise in Generative AI (LLMs & VLMs), High-Level Task-Planning, and ... testing) * Experience with deploying edge-to-cloud hybrid systems is a strong plus * Team spirit ...

New

helsing.ai

$80.64 - $115.19/hr

Experience deploying AI software to production including testing, quality assurance, and monitoring ... generative AI, or deployment infrastructure. The defence industry is entering the most exciting ...

New

Booz Allen Hamilton

AI/ML Engineer, Senior

Dayton, OH · On-site

$99 - $225/hr

Conduct model optimization, tuning, versioning, and A/B testing to ensure robust mission impact ... learning, generative AI, or reinforcement learning. * 5+ years of experience building AI/ML ...

Edenred Finland Oy

$81 - $104/hr

... MCP) and Generative AI, ideally demonstrated through the development and deployment of AI ... testing and iterating AI solutions * Technical curiosity combined with practical scripting ...

New

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Generative Ai Testing information

What is generative AI testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What are the key skills and qualifications needed to thrive as a generative AI testing specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

What are popular job titles related to Generative Ai Testing jobs in Ohio?

For Generative Ai Testing jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Ohio look for?

The top searched job categories for Generative Ai Testing jobs in Ohio are:

What cities in Ohio are hiring for Generative Ai Testing jobs?

Cities in Ohio with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 8% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Agentic AI Engineer (human)

NEURA Robotics

On-site

$100 - $130/hr

Other

Posted yesterday

New

Job description

The evolution of cognitive robotics is moving beyond static commands toward autonomous agency. At NEURA Robotics, we aren't just building machines; we are developing intelligent entities capable of independent reasoning, multi-step planning, and real-time environmental adaptation.

Your mission & challenges
  • Agentic Orchestration & Framework Design: You will develop the conceptual design and main conversational AI agent. You will select and implement the core AI and software frameworks to handle multi-agent orchestration.
  • The Intelligence Sequence: You will design systems that manage the end-to-end cognitive loop, translating multimodal inputs and contextual reasoning into autonomous action planning, skill orchestration, and real-time user feedback.
  • System Integration & Interface Creation: You will architect robust interface pipelines that allow sub-agents to seamlessly connect to the main conversational agent
  • Strategic Project Management: You will independently identify, evaluate, and manage high-impact AI initiatives, ensuring that emerging agentic technologies are successfully integrated into the NEURA ecosystem.
  • Collaborative Ecosystem Building: You coordinate and manage collaboration with internal IT units, cross-functional hardware/software teams, and external partners to ensure smooth end-to-end industrialization.
What we can look forward to
  • An excellent Master’s or PhD in Computer Science, Informatics, Robotics, Physics, or a related field ideally field
  • A proven track record: Your projects show measurable impact.
  • Strong programming skills in Python.
  • Proven experience in implementing and industrializing AI solutions, with deep, hands-on experience in open-source agentic and orchestration frameworks
  • Strong methodological expertise in Generative AI (LLMs & VLMs), High-Level Task-Planning, and Natural Language Processing, with a focus on translating human intent into actionable, step-by-step logic
  • Proven experience in API/Interface design and systems architecture to enable the seamless integration of modular, distributed sub-agents
  • Proficiency in software development best practices (clean code, object-oriented programming, DevOps, testing)
  • Experience with deploying edge-to-cloud hybrid systems is a strong plus
  • Team spirit, initiative, and the ability and willingness to explore new paths.
  • Excellent English skills; German is optional but welcome.
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