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Generative Ai Testing Jobs in Chicago, IL (NOW HIRING)

Whiztek Corp

AI Engineer

Schaumburg, IL · On-site

Agentic AI/AI Engineer - Generative AI & Machine Learning Location:  Schaumburg, IL (Hybrid - 3 ... Familiar with functional and non-functional testing of AI/ML applications and operationalizing it ...

Hendrickson USA, LLC

AI Intern

Woodridge, IL · On-site

Essential Functions: * Assist in the design, development, testing, and deployment of AI-powered applications for enterprise use cases, including Generative AI solutions. * Assist in implementing LLM ...

Deloitte

Lead Generative AI Data Engineer III

Chicago, IL

$105K - $139K/yr

Lead the design, development, testing, and deployment of machine learning and artificial ... Manage AI engineering workstreams by assigning work, reviewing deliverables, and driving quality ...

Writer

AI deployment engineer (Central)

Chicago, IL · On-site

$131K - $166K/yr

... generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin ... Early-detection cancer testing through Galleri * Flexible spending account and dependent FSA ...

Contruent

AI Engineer

Naperville, IL

Design and implement machine learning and generative AI solutions using cloud services such as AWS ... Ensure responsible AI design, including model monitoring, bias testing, and performance validation.

Contruent

AI Engineer

Naperville, IL · On-site

$125K - $175K/yr

Design and implement machine learning and generative AI solutions using cloud services such as AWS ... Ensure responsible AI design, including model monitoring, bias testing, and performance validation.

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Generative Ai Testing information

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How much do generative ai testing jobs pay per hour?

As of Jul 20, 2026, the average hourly pay for generative ai testing in Chicago, IL is $55.35, according to ZipRecruiter salary data. Most workers in this role earn between $45.58 and $63.41 per hour, depending on experience, location, and employer.

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 much do AI testers get paid?

AI testers, involved in evaluating and validating generative AI models, typically earn salaries ranging from $60,000 to $120,000 annually depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in machine learning and data analysis can earn higher wages.

Is AI testing a good career?

AI testing, including roles like Generative AI Testing, is a growing field with increasing demand for skills in machine learning, data analysis, and software quality assurance. It offers opportunities in tech companies, research labs, and startups, often requiring knowledge of AI frameworks and testing tools. The career can be stable and rewarding for those with technical expertise and an interest in AI development.

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 salary of generative AI tester?

The salary of a generative AI tester typically ranges from $70,000 to $120,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in AI and machine learning can earn higher salaries. Certifications in AI or related fields can also influence compensation.

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.

How do I become an AI tester?

To become an AI tester, you should have a strong understanding of machine learning concepts, programming skills in languages like Python, and experience with data annotation and model evaluation. Familiarity with AI tools, testing frameworks, and quality assurance processes is also important. Gaining relevant certifications or training in AI and software testing can enhance your qualifications.

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 popular job titles related to Generative Ai Testing jobs in Chicago, IL? For Generative Ai Testing jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in Chicago, IL look for? The top searched job categories for Generative Ai Testing jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Generative Ai Testing jobs? Cities near Chicago, IL with the most Generative Ai Testing job openings:
Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Chicago, IL as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $115,119 per year, or $55.3 per hour.
Agentic AI/AI Engineer - Generative AI & Machine Learning

Agentic AI/AI Engineer - Generative AI & Machine Learning

Whiztek Corp

Schaumburg, IL • On-site

$96K - $131K/yr

Other

Posted 26 days ago

Job description

Role: Agentic AI/AI Engineer - Generative AI & Machine Learning

Location:  Schaumburg, IL (Hybrid)

Long Term Contract

Job Summary:

We are seeking a highly motivated and adaptable AI Engineer to join our innovative team. The ideal candidate will have a strong background in both Generative AI and traditional Machine Learning, with a proven ability to work on existing applications and develop new solutions. You will play a key role in migrating and enhancing our AI-driven projects, leveraging Large Language Models (LLMs), and building intelligent agents. This is an exciting opportunity for a forward-thinking engineer who is passionate about experimenting with cutting-edge technologies and evolving in a fast-paced environment.

Key Responsibilities:

  • Develop, maintain, and enhance existing applications that utilize both Generative AI and traditional Machine Learning.
  • Work extensively with Large Language Models (LLMs) to build and refine AI-powered features.
  • Design, create, and deploy intelligent agents to automate and optimize processes.
  • Collaborate with stakeholders to understand and translate business requirements into technical specifications for AI engineering projects.
  • Conduct experiments, implement new technologies, and contribute to the rapid evolution of our AI capabilities.
  • Lead the migration of existing projects, including those with agents and LLMs, to our Google Cloud Platform (Google Cloud Platform) environment.
  • Engage in full-stack development, with a focus on Python for backend services and React for frontend interfaces.
  • Perform data analysis using SQL to query and manipulate data from MS SQL Server, MySQL, and other relational databases.

Required Qualifications:

  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • A minimum of 2-3 years of professional experience in an AI or Machine Learning engineering role.
  • Experience with Python is a must.
  • Demonstrated experience with concepts such as MCP, RAG, Semantic search, Generative AI, LLMs, and building agent-based systems.
  • Ability to stay up to date with new and upcoming technologies around AI development (ex: Agentic RAG)
  • Strong proficiency in Python for backend development and machine learning.
  • Solid experience with React for frontend development.
  • Expertise in SQL and experience working with relational databases such as MS SQL Server and MySQL.
  • Hands-on experience with Google Cloud Platform AI/ML services, including BigQuery, Google SQL and other technologies and APIs within Google Cloud Platform.
  • Ability to quickly grasp new requirements, experiment with new technologies, and adapt to a rapidly changing environment.
  • Experience in taking over existing AI/ML applications from other teams.
  • Estimate at a high-level cost of usage in Google Cloud Platform for applications hosted/deployed  
  • Familiar with functional and non-functional testing of AI/ML applications and operationalizing it in production 

Other Qualifications:

  • Familiarity with Amazon Web Services (AWS), LLM models trending in the industry.
  • A portfolio of projects demonstrating your expertise in AI and full-stack development. 

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