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Adversarial Machine Learning Jobs in Laurel, MD (NOW HIRING)

Cmu

AI Security Software Engineer

Arlington, VA · On-site +1

Additionally, we work in generative AI and large language models, data visualization, security analysis of AI systems, and adversarial machine learning. We have access to a wide variety of cyber ...

Cmu

Senior AI Security Software Engineer

Arlington, VA · On-site +1

Additionally, we work in generative AI and large language models, data visualization, security analysis of AI systems, and adversarial machine learning. We have access to a wide variety of cyber ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

Our adversarial red teaming, model evaluations, and intelligence collection enable engineering ... We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ...

HiddenLayer

AI Solutions Architect- Federal

Washington, DC · Remote

$71.25 - $94/hr

Maintain deep currency in adversarial machine learning and the evolving AI threat landscape, and raise the technical bar of everyone around you. WHO YOU ARE: * 5+ years in solutions architecture ...

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How much do adversarial machine learning jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for adversarial machine learning in Laurel, MD is $21.15, according to ZipRecruiter salary data. Most workers in this role earn between $18.61 and $22.64 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals working in adversarial machine learning roles?

Adversarial Machine Learning professionals often face the challenge of staying ahead of rapidly evolving attack techniques that can compromise model integrity and security. Managing the balance between model performance and robustness is another key difficulty, as defenses against adversarial attacks can sometimes reduce accuracy or increase computational costs. Collaboration with data scientists, security teams, and software engineers is vital for developing resilient models and implementing effective defenses. Staying current with the latest research and tools is essential for success in this dynamic field.

What are the key skills and qualifications needed to thrive as an adversarial machine learning specialist, and why are they important?

To excel in Adversarial Machine Learning, you need a strong background in machine learning, deep learning, statistics, and computer science, typically supported by an advanced degree in a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial attack and defense libraries, and knowledge of security protocols are crucial. Creative problem-solving, critical thinking, and strong communication skills help in designing robust models and explaining complex threats to stakeholders. These competencies are vital to anticipate vulnerabilities, safeguard AI systems, and ensure the reliability of machine learning models in real-world applications.

What is the difference between Adversarial Machine Learning vs Data Scientist?

AspectAdversarial Machine LearningData Scientist
CredentialsKnowledge of machine learning, cybersecurity, and threat detectionDegree in data science, statistics, or related fields
Work EnvironmentResearch labs, cybersecurity teams, AI developmentBusiness analytics, data analysis, model development
Industry UsageAI security, cybersecurity, machine learning researchBusiness, finance, healthcare, tech companies

Adversarial Machine Learning focuses on understanding and defending AI models against malicious inputs, often within cybersecurity contexts. Data Scientists analyze data to extract insights, build models, and support decision-making across various industries. While both roles require machine learning knowledge, Adversarial Machine Learning emphasizes security and robustness, whereas Data Scientists focus on data analysis and predictive modeling.

What is adversarial machine learning?

Adversarial machine learning is a field of study focused on understanding and defending against attacks that manipulate machine learning models by feeding them deceptive input, known as adversarial examples. These attacks can cause models to make incorrect predictions, raising concerns about the security and reliability of AI systems, especially in critical applications like image recognition and autonomous vehicles. Researchers in this area develop techniques to detect, prevent, and mitigate these vulnerabilities to make machine learning systems more robust.
What are popular job titles related to Adversarial Machine Learning jobs in Laurel, MD? For Adversarial Machine Learning jobs in Laurel, MD, the most frequently searched job titles are:
What job categories do people searching Adversarial Machine Learning jobs in Laurel, MD look for? The top searched job categories for Adversarial Machine Learning jobs in Laurel, MD are:
What cities near Laurel, MD are hiring for Adversarial Machine Learning jobs? Cities near Laurel, MD with the most Adversarial Machine Learning job openings:
Adversarial Machine Learning jobs near you

Senior Machine Learning Research Scientist - Secure AI Lab

Carnegie Mellon University

Arlington, VA • On-site

$113K - $144K/yr

Full-time

Re-posted 21 days ago

Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

67th of 618 rated colleges and universities

Job description

Job Summary:
Carnegie Mellon University is a leading institution in research and education, and they are seeking a Senior Machine Learning Research Scientist for their Secure AI Lab. The role involves conducting research on vulnerabilities of AI and ML algorithms and developing solutions to secure these systems against adversaries.
Responsibilities:
• Identifying and investigating emerging AI and AI-adjacent technologies.
• Performing and publishing impactful original research in the field of AI and ML algorithm vulnerabilities and securing against those vulnerabilities.
• Adapting and applying existing research in the field to solve real-world problems.
• Transitioning and providing guidance on AI capabilities to government sponsors.
• Hands-on research: You'll conduct and lead novel research in applied machine learning and artificial intelligence.
• Solution development: You'll work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.
• Strategy: You'll work with the leadership team and colleagues to plan, develop, and carry out an overall research strategy, and to influence the national research agenda regarding future technology.
• Collaboration: You'll actively participate on teams of software developers, researchers, designers, and technical leads. You'll build relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research directions.
• Mentoring: You'll contribute to improving the overall technical capabilities of the Division by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI AI Division.
Qualifications:
Required:
• A bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD with five (5) years of experience
• Willingness to work onsite at an SEI facility 5 days per week.
• Be able to obtain and maintain an active Department of War security clearance.
• Willing to travel up to 25% of the time to locations outside of your home location. Travel sites include SEI offices in Pittsburgh and Washington, D.C., sponsor sites, and conferences.
• Comprehensive knowledge of machine learning; previous experience in adversarial machine learning preferred but not required
• A track record of conducting research and applying scientific methods to solve difficult problems
• Experience leading research projects in novel areas with limited previous work to build upon
• Ability to work with leadership to plan, develop, and deliver an overall research strategy
• Strong written and verbal communication skills; ability to convey complex technical ideas in a layperson’s terms
• Proficiency in writing funding proposals or pitching ideas for new research projects
• Ample experience with publishing written or technical artifacts showcasing your work
• Strong collaboration skills for working with colleagues and sponsors
• Willingness to guide and mentor junior team members
Preferred:
• Previous experience in adversarial machine learning
Company:
Carnegie Mellon University is a research university offering programs and research across engineering, science, arts, and business. Founded in 1900, the company is headquartered in Pittsburgh, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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