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Generative Ai Testing Jobs in Virginia (NOW HIRING)

Carmax

Director, AI/ML Engineering

Richmond, VA

Lead the adoption of generative AI technologies (including large language models and multimodal AI ... rapid testing, and learning, with a relentless focus on delivering customer value * Establish ...

CarMax, Inc.

Director, AI/ML Engineering

Richmond, VA · On-site

Lead the adoption of generative AI technologies (including large language models and multimodal AI ... rapid testing, and learning, with a relentless focus on delivering customer value * Establish ...

MITRE

Intermediate AI and Decision Engineer

Mclean, VA

$100K - $137K/yr

... generative and agentic AI, decision science, human machine teaming, cognitive science, AI testing and evaluation, multi-agent systems, knowledge-based reasoning, automated planning, semantics, and ...

MITRE

Senior AI and Decision Engineer

Mclean, VA · Hybrid

$143K - $179K/yr

... generative and agentic AI, decision science, human machine teaming, cognitive science, AI testing and evaluation, multi-agent systems, knowledge-based reasoning, automated planning, semantics, and ...

CGI

AI/ML Engineer

Fairfax, VA

This role blends full stack engineering with modern AI/ML, integrating generative AI and advanced ... CI/CD with Jenkins/GitLab/Bitbucket; testing frameworks; package managers. o Cloud: Production ...

Kasmo Global

Sr Python AI/ML Engineer

Reston, VA

... testing, debugging, and optimization. 2. Generative AI Development: • Develop and fine-tune generative AI models using frameworks like TensorFlow, PyTorch, or Hugging Face. • Implement machine ...

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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.

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 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 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 Virginia? For Generative Ai Testing jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in Virginia look for? The top searched job categories for Generative Ai Testing jobs in Virginia are:
What cities in Virginia are hiring for Generative Ai Testing jobs? Cities in Virginia with the most Generative Ai Testing job openings:
Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Virginia as of June 2026, with employment types broken down into 10% Internship, 70% Full Time, 15% Part Time, and 5% Temporary. Highlights an 80% In-person, 5% Hybrid, and 15% Remote job distribution.

CDAO - Enterprise - Generative AI Program Manager

DoW Chief Digital and Artificial Intelligence Office (CDAO)

Arlington, VA • On-site

Full-time

Posted 20 days ago

Job description

Job Summary:
The Chief Digital and Artificial Intelligence Office (CDAO) is dedicated to accelerating the adoption of data, analytics, and artificial intelligence across the Department of War. The Generative AI Program Manager will lead the development and integration of cutting-edge AI capabilities into DoW workflows, managing software engineering processes and collaborating with various stakeholders to enhance the application of AI technologies.
Responsibilities:
• Lead the acquisition and development of software technologies to pilot, experiment, and deploy Frontier AI into critical DoW workflows.
• Manage, budget, plan, and execute a large software development program involving multiple industry software development teams.
• Provide subject matter expertise to inform best practices, guidance, and direction on DoW applications of generative and traditional AI technologies.
• Provides subject matter expertise to advise DoW partners on application of policy, best practices, standards, principles, theories, and techniques in order to ensure successful and effective development, experimentation, assurance, and fielding of generative and traditional AI applications.
• Work across a diverse and cross-functional team of technical experts, operational end-users, software developers, and DoW partners to deliver capability that directly supports DoW missions.
Qualifications:
Required:
• U.S. Citizenship is required.
• Candidate is encouraged to provide e-portfolio, project samples, Github, etc. to their submission package.
• Males born after 12-31-59 must be registered or exempt from Selective Service.
• This position is subject to provisions of the WHS/OSD Priority Placement Program.
• Applicants for employment are covered by federal laws and Presidential Executive Orders designed to safeguard federal employees and job applicants from discrimination based on race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), political affiliation, military service, or other non-merit-based factors.
• A three-year trial period may be required if not previously completed a trial or probationary period in the excepted or competitive service.
• Must be determined suitable for federal employment.
• Required to participate in the direct deposit program.
• This position is subject to pre-employment and random drug testing.
• This position requires a Top Secret/ Sensitive Compartmented Information (SCI) security clearance.
• If you are a veteran claiming veteran's preference, as defined by Section 2108 of Title 5 U.S.C., you must submit documents verifying your eligibility with your application package.
• This position may require work other than normal duty hours, which may include evenings, weekends, and/or holidays and/or mandatory overtime.
• This position may occasionally require travel away from the normal duty station via military or commercial aircraft.
Company:
Welcome to the official account for the U.S. Department of War's Chief Digital and Artificial Intelligence Office. Founded in 2022, the company is headquartered in Washington, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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