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Adversarial Machine Learning Jobs (NOW HIRING)

Weekday AI

AI Safety & Red Teaming Specialist

Required Qualifications * 2+ years of experience in AI Safety, Adversarial Machine Learning, LLM Red Teaming, AI Security, or a related field. * Hands-on experience researching, testing, or ...

University of Idaho

Postdoctoral Researcher

Moscow, ID · On-site

$58K/yr

The postdoctoral researcher will conduct cutting-edge research in areas such as cyber-physical systems security, protection of critical infrastructure, and adversarial machine learning. The position ...

OVA.Work

Responsible AI Engineer

... machine learning models. • Develop testing frameworks for AI robustness, adversarial risks, and model safety. • Evaluate Large Language Models (LLMs) and Generative AI applications for ...

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 ...

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How much do adversarial machine learning jobs pay per hour?

As of Aug 27, 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 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 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.

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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 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,363 per year, or $21.3 per hour.

Senior Machine Learning Research Scientist - SAIL

Pittsburgh, PA • On-site

Software Engineering Institute | Carnegie Mellon University
See more jobs at Software Engineering Institute | Carnegie Mellon Universityexternal

$95K - $121K/yr

Full-time

Re-posted 9 days ago

Job description

Job Summary:
Carnegie Mellon University is a leading research institution focused on advancing artificial intelligence and machine learning. They are seeking a Senior Machine Learning Research Scientist to conduct research on AI vulnerabilities and develop strategies to secure AI systems against adversaries.
Responsibilities:
• 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, and maintaining AI capabilities
• identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape
• conduct and lead novel research in applied machine learning and artificial intelligence
• work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders
• 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
• actively participate on teams of software developers, researchers, designers, and technical leads
• build relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research directions
• 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 in 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:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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