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Adversarial Machine Learning Jobs in North Carolina

Explore a range of AI security problems, such as LLM and agent security, adversarial testing, model ... Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Cybersecurity or ...

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Adversarial Machine Learning information

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.

What job categories do people searching Adversarial Machine Learning jobs in North Carolina look for?

The top searched job categories for Adversarial Machine Learning jobs in North Carolina are:

What cities in North Carolina are hiring for Adversarial Machine Learning jobs?

Cities in North Carolina with the most Adversarial Machine Learning job openings:

Senior AI Security Researcher

Nvidia

Durham, NC • On-site

Full-time

Re-posted 2 days ago


Key responsibilities

  • Develop and answer open-ended AI security research questions that help understand, measure, and reduce risk in AI systems.

  • Build methods, prototypes, evaluations, or tools to identify how AI systems can fail under adversarial conditions and develop mitigations.

  • Translate research findings into practical outcomes such as proof-of-concept demonstrations, benchmarks, technical guidance, and secure deployment recommendations.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA is looking for a Senior AI Security Researcher to help define how frontier AI systems, agentic applications, and AI-enabled security automation are tested, attacked, defended, and safely deployed. You will build new methods, tools, evaluations, and proofs of concept that help NVIDIA understand and reduce security risk across AI models, AI platforms, autonomous agents, cloud services, developer tooling, and accelerated computing systems. We are looking for a researcher who can move fluidly from open-ended research questions to application within working systems: someone who can discover novel failure modes, build rigorous evaluation harnesses, prototype adversarial and defensive techniques, and turn findings into practical mitigations for engineering teams.

The right person may come from AI security, ML security, malware data science, cyber-defense research, adversarial ML, LLM security, offensive security, threat hunting, or applied security research at scale. What You'll Be Doing: Develop and answer open-ended AI security research questions that helps NVIDIA understand, measure, and reduce risk in frontier models, agentic systems, AI platforms, and AI-enabled products. Develop practical methods, prototypes, evaluations, or tools that reveal how AI systems can fail under adversarial conditions and how those risks can be mitigated.

Explore a range of AI security problems, such as LLM and agent security, adversarial testing, model evaluation, cyber-defense automation, vulnerability discovery, secure deployment, or autonomous response. Translate research into usable outcomes for engineering and security teams, including proof-of-concept demonstrations, benchmarks, technical guidance, mitigations, and secure-by-design recommendations. Collaborate across offensive security, product security, AI research, platform, cloud, and infrastructure teams to connect research insights with NVIDIA's highest-impact security priorities.

Help shape NVIDIA's AI-security research strategy by mentoring others, identifying emerging risks, and building repeatable practices for evaluating and defending AI systems. What We Need to See: 12+ years of experience in AI security, cybersecurity research, applied ML research, offensive security, cyber defense, or related technical fields. Demonstrated record of original research and practical impact, such as deployed security ML systems, AI-security evaluations, CVEs, patents, publications, conference talks, open-source tools, production mitigations, or funded research programs.

Hands-on ability to build working research systems in Python and modern ML/data tooling such as PyTorch, JAX, TensorFlow, scikit-learn, Pandas, NumPy, Spark, BigQuery, or comparable platforms. Experience with one or more AI-security areas: LLM security, adversarial ML, model evaluation, agent security, prompt injection, model backdoors, data poisoning, model abuse, secure RAG, synthetic data, or AI-enabled security automation. Strong cybersecurity foundation, including threat modeling, adversary simulation, exploit or vulnerability research, malware analysis, network defense, threat hunting, detection engineering, digital forensics, secure code review, or incident-response automation.

Ability to work across ambiguous research problems and practical product constraints, translating findings into prioritized recommendations and measurable security outcomes. Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Cybersecurity or a related field. Experience leading AI-security research for major models, AI platforms, security products, or large-scale production systems.

A track record of building security ML systems that operate at real-world scale, Ways to Stand Out from the Crowd: Published work or public technical leadership in AI security, malware data science, adversarial ML, LLM security, cyber-defense automation, or offensive AI. Experience developing benchmarks, challenge datasets, red-team tools, evaluation suites, or simulation environments for AI and security systems. Deep knowledge of attacker tradecraft, including living-off-the-land techniques, supply-chain abuse, application-layer AI attacks, data exfiltration, and abuse of autonomous tooling.

Experience with low-level systems security. History of mentoring researchers, winning or leading research programs, filing patents, publishing papers, or speaking at major security and AI venues. In this role, your research will help NVIDIA build AI systems that are not only powerful, but trustworthy, resilient, and secure.

You will work with world-class researchers, engineers, and security teams on problems that matter to NVIDIA's products, customers, and the broader AI ecosystem. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits. Applications for this job will be accepted at least until September 5, 2026. This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US