Alpharetta, GA · On-site
Collaborate closely with developers and program managers to prioritize and resolve issues promptly ... Generative AI implementations. * Stay updated on new testing approaches, tools, and strategies.
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Alpharetta, GA · On-site
Collaborate closely with developers and program managers to prioritize and resolve issues promptly ... Generative AI implementations. * Stay updated on new testing approaches, tools, and strategies.
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g ... Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ...
| Aspect | Manager Generative Ai | Data Scientist |
|---|---|---|
| Required Credentials | Advanced degrees in AI, Computer Science, or related fields; experience with AI project management | Degree in Data Science, Statistics, Computer Science, or related fields; proficiency in programming and statistical analysis |
| Work Environment | Leads AI teams, collaborates with product and engineering teams, oversees AI projects | Analyzes data, develops models, and provides insights; often works independently or in small teams |
| Employer & Industry Usage | Tech companies, AI startups, large enterprises implementing AI solutions | Research institutions, tech firms, finance, healthcare, and other data-driven industries |
The main difference is that a Manager Generative Ai oversees AI projects and teams focusing on generative models, while a Data Scientist primarily analyzes data and develops models. Managers focus on leadership and strategy, whereas Data Scientists focus on technical analysis and model development.
Contractor
Re-posted 7 days ago
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
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