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Adversarial Machine Learning Jobs (NOW HIRING)

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Generative Adversarial Architectures. Preferred qualifications * MS. or PhD in Machine Learning, or related field * Extensive AWS or GCP experience putting scalable Machine Learning systems into ...

Cmu

Senior AI Security Software Engineer

Pittsburgh, PA · 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 ...

Cmu

AI Security Software Engineer

Pittsburgh, PA · 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

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 ...

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How much do adversarial machine learning jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for adversarial machine learning in the United States is $21.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $22.84 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.
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Adversarial Machine Learning jobs near you
Infographic showing various Adversarial Machine Learning job openings in the United States as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $44,363 per year, or $21.3 per hour.

Senior Machine Learning Research Scientist - Secure AI Lab

Carnegie Mellon University

Pittsburgh, PA

$88K - $121K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 17 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 616 rated colleges and universities

Job description

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.

As our government customers adopt AI and machine learning toprovideleap-ahead mission capabilities, we

  • build real-world, mission-scale AI capabilities through solving practical engineering problems

  • discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities

  • prepare our customers to be ready for the unique challenges of adopting, deploying, using, andmaintainingAI capabilities

  • identifyand investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape

Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.

Overview:As a Senior Machine LearningResearch Scientist,you will specialize inconductingresearch into the vulnerabilities of AIandML algorithms and securing against those vulnerabilities.

TheSecure AILab within the SEI's AI Division focuses on improving the security and robustness of AI systems. As part of the world-class research community at Carnegie Mellon University, theSecure AILabconducts and appliescutting-edgeresearch toprotectAI systems fromadversaries who aim to manipulatethe systemto learn, do, or revealsomething itisn'tsupposed to.

TheSecure AILab consists of machine learning research scientists, machine learning engineers, and software developers who work together to solve problems in the following areas:

  • Counter AI Research:Study threat models targeting AIandML algorithms,understand the behaviors of AI algorithms,identifyweak points, and design novel ways to subvert AIandML systems.

  • AIandMLAlgorithm DefenseResearch:Createpractical mitigations and defenses forobservedattacksaffecting AIandML algorithmsand evaluate the effectiveness ofdefensivetechniques.

  • AppliedAdversarial Machine Learning:Advance the state of the art inadversarialmachinelearningby developing and transitioning capabilities to government sponsors.

Your day-to-day research tasks will include:

  • Identifyingandinvestigatingemerging AI and AI-adjacent technologies.

  • Performing andpublishingimpactful original research in the field ofAIandML algorithm vulnerabilities and securing against those vulnerabilities.

  • Adapting andapplyingexisting research in the field to solve real-world problems.

  • Transitioning andprovidingguidanceonAI capabilities to government sponsors.

Duties:

  • Hands-on research:You'llconduct and lead novel research in applied machine learning and artificial intelligence.

  • Solution development:You'llwork with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.

  • Strategy:You'llwork withthe leadership teamand colleagues to plan, develop, and carry out an overall research strategy, and to influence the national research agendaregardingfuture technology.

  • Collaboration:You'llactivelyparticipateon teams of software developers, researchers, designers, and technical leads.You'llbuild relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs,possible solutions, and research directions.

  • Mentoring:You'llcontribute to improving the overall technical capabilities of the Divisionby mentoring and teaching others,participatingin design (software and otherwise) sessions, and sharing insights and wisdom across the SEIAIDivision.

Knowledge andExperience

  • Comprehensiveknowledge ofmachine learning;previousexperiencein adversarial machine learningpreferredbut notrequired

  • A track recordofconducting research and applying scientific methodsto solvedifficult problems

  • Experienceleadingresearchprojectsinnovelareaswith limitedpreviouswork to build upon

  • Abilityto work with leadership to plan, develop, anddeliveran overallresearchstrategy

  • Strong written and verbal communication skills;abilityto convey complex technical ideasinalayperson's terms

  • Proficiencyinwritingfunding proposalsorpitchingideas fornew researchprojects

  • Ampleexperience with publishingwritten or technicalartifactsshowcasingyour work

  • Strong collaboration skills forworkingwith colleagues and sponsors

  • Willingnesstoguide andmentorjunior team members

Requirements

  • 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 andmaintainan 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.

Joining the CMU team opens the door to an array of exceptional benefits.

Benefits eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits, take well-deserved breaks with ample paid time off and observed holidays, and rest easy with life and accidental death and disability insurance.

Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team to help navigate childcare needs, fitness center access, and much more!

For a comprehensive overview of the benefits available, explore our Benefits page.

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it's about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in an exciting opportunity with an exceptional organization?! Apply today!

Location

Arlington, VA, Pittsburgh, PA

Job Function

Software/Applications Development/Engineering

Position Type

Staff - Regular

Full Time/Part time

Full time

Pay Basis

Salary

More Information:

  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.

  • Click here to view a listing of employee benefits

  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.

  • Statement of Assurance

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