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Generative Ai Testing Jobs in Maryland (NOW HIRING)

RAKS Group LLC

Gen AI Developer

Woodlawn, MD · On-site

Conduct code reviews, testing, and debugging to ensure application reliability and performance. Stay current with emerging technologies and best practices in Generative AI and full stack development.

Morgan Stanley

VP, AI Compliance Officer

Baltimore, MD · On-site

$108K - $185K/yr

What you'll do in the role: > Advise Wealth Management Generative AI and Platforms teams on AI ... Testing teams. > Collaborate with Policy and Training teams to draft, implement, and maintain ...

Dcode Talent LLC

GenAI Engineer

Woodlawn, MD · On-site

Incorporating generative AI models into existing software applications and products. · Research ... control, and testing. · Problem-solving, analytical, and critical thinking skills. · Strong ...

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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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Infographic showing various Generative Ai Testing job openings in Maryland as of July 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution.

Staff Machine Learning Engineer - Generative AI

Xometry

Gaithersburg, MD • Hybrid

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 24 days ago

Job description

Xometry is seeking a Staff Machine Learning Engineer to lead our Generative AI efforts. This is a rare opportunity to shape the future of manufacturing by applying cutting-edge AI research to real-world problems: from multimodal document understanding, to extracting structured data from technical drawings, to building new ways of reasoning across text, images, and 3D data. If you're passionate about building state-of-the-art AI systems and want to see your work have immediate business and customer impact, we'd love to talk.

How You'll Contribute:

  • Lead with vision - Set the technical direction for our Generative AI team, establish best practices, and inspire high-impact innovation
  • Drive strategy - Help shape the AI roadmap, identifying the most valuable opportunities to apply generative AI across Xometry's marketplace
  • Build cutting-edge models - Develop and deploy large language and generative models for multimodal document processing and structured data extraction
  • Innovate across modalities - Explore new ways to combine text, images, and 3D data to unlock smarter, faster solutions
  • Engineer at scale - Create data pipelines and training workflows that can handle massive, complex datasets
  • Deploy in the cloud - Use AWS and other platforms to train, optimize, and deploy models into production at scale
  • Collaborate widely - Work with engineers, product leaders, and business teams to bring AI solutions into real products and customer workflows
  • Mentor and grow - Guide teammates on advanced ML methods, model architecture, and best practices, elevating the entire team
  • Stay ahead - Keep up with the latest generative AI and deep learning research, and bring fresh ideas into production

What You'll Bring to Xometry:

  • Bachelor's degree required; advanced degree (M.S. or PhD) in Computer Science, Machine Learning, AI, or related field is a big plus
  • 5+ years of experience in machine learning or data science, with deep expertise in generative models, LLMs, or computer vision
  • Strong track record working with large-scale language and vision models (Transformers, GPT, VLMs)
  • Hands-on experience with multimodal data (text, images, 3D)
  • Proficiency in Python and key ML libraries (PyTorch, TensorFlow, pandas, NumPy)
  • Solid grounding in probability, statistics, and optimization for generative modeling
  • Experience deploying ML and AI models using cloud microservice architecture (AWS preferred)
  • Strong software engineering skills, including object oriented programming, testing, version control, CI/CD best practices and IaC (terraform preferred)
  • A proven ability to communicate effectively with all levels of the organization, from executives to product managers and various stakeholders
  • Background in manufacturing, supply chain, or related industries is a plus - but curiosity and drive matter more
  • Must be a U.S. Citizen or Green Card holder (ITAR compliance)

The estimated base salary range for new hires into this role is $140,000-$230,000 annually + bonus depending on factors such as job-related skills, relevant experience, and location.  We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

#LI-Hybrid

Xometry logo

About Xometry

Sourced by ZipRecruiter

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Industry

Software development

Company size

501 - 1,000 Employees

Headquarters location

Gaithersburg, MD, US

Year founded

2013

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