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Generative Ai Testing Jobs in Georgia (NOW HIRING)

Deloitte

Lead Generative AI Data Engineer III

Atlanta, GA · On-site

$98K - $129K/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 ...

Deloitte

Lead Generative AI Data Engineer III

Atlanta, GA · On-site

$98K - $129K/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 ...

Elevance Health

AI Machine Learning Scientist

Atlanta, GA · On-site +1

Design, develop, and deploy AI/ML and Generative AI solutions that address business and operational ... Implement evaluation frameworks and automated testing strategies to measure model quality, accuracy ...

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Generative Ai Testing information

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.
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Generative Ai Testing jobs near you
QA with Generative AI

QA with Generative AI

Precision Technologies Corp

Alpharetta, GA • On-site

Contractor

Posted 18 days ago

Job description

Job Description:

The Quality Engineer for Generative AI will be responsible for ensuring the quality and reliability of the AI systems developed under the EDD GENAI project. This role involves close collaboration with the development team and key stakeholders to understand project requirements and develop comprehensive test plans. The Quality Engineer will conduct various types of testing, including unit testing, component testing, and multi-component testing, while also automating these tests to improve efficiency and reliability.

Key Responsibilities:

•Collaborate as part of a DBA fleet, focusing on QE processes with a strong emphasis on automation execution using various tools and techniques.

•Develop test strategies and plans for Generative AI implementations.

•Design and execute test cases to validate the functionality, performance, and reliability of Generative AI solutions.

•Work with stakeholders to identify testing requirements and priorities.

•Identify and document defects, issues, and risks related to Generative AI implementations.

•Collaborate closely with developers and program managers to prioritize and resolve issues promptly.

•Develop and maintain automated test scripts and frameworks for efficient and effective testing.

•Drive continuous improvement and best practices in testing methodologies and processes for Generative AI implementations.

•Stay updated on new testing approaches, tools, and strategies.

Required Skills:

•8+ years of proven work experience in Quality Engineering.

•Experience integrating LLM automation tests into CI/CD pipelines and hands-on experience in prompt engineering concepts.

•Proven experience in developing and implementing automation frameworks for Large Language Models.

•Strong programming skills in languages such as Python, Java, or similar.

•Experience with popular testing tools and frameworks (e.g., Selenium, JUnit, TestNG).

•Knowledge of Natural Language Processing (NLP) concepts and techniques.

•Familiarity with CI/CD pipelines and version control systems (e.g., Jenkins, Git).

•Strong problem-solving and analytical skills.

•Experience with automation technologies, including Selenium, JUnit, Gherkin, JMeter, and scripting languages such as Java.

Educational Qualification:

•Minimum BS degree in Computer Science, Engineering, or a related field.

Join our team and contribute to the development of cutting-edge AI solutions