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Adversarial Machine Learning Jobs in Texas (NOW HIRING)

Adversarial Testing: Experience leading or participating in red team exercises, penetration testing, or threat modeling specifically tailored to machine learning models and AI systems. Cross ...

Adversarial Testing: Experience leading or participating in red team exercises, penetration testing, or threat modeling specifically tailored to machine learning models and AI systems. Cross ...

Sr. Security AI/ML Engineer

Plano, TX · On-site

$109K - $150K/yr

Conduct architecture reviews of AI and machine learning solutions proposed by engineering and data ... Fundamentals on emerging AI threats, adversarial techniques, and evolving security frameworks What ...

Adversarial Testing: Experience leading or participating in red team exercises, penetration testing, or threat modeling specifically tailored to machine learning models and AI systems. Cross ...

Content Developer (SIEM Cyber Security)

San Antonio, TX · On-site

$110K - $115K/yr

Develop dashboards and visualizations to identify adversarial activity. (CDRL A007) * Use log data ... GMLE Certification (GIAC Machine Learning Engineer) OR Degree in Computer Science * More than 5 ...

Experience in adversarial simulation and red-teaming methodologies * Demonstrated ability to ... Please note that Meta may leverage artificial intelligence and machine learning technologies in ...

Experience in adversarial simulation and red-teaming methodologies * Master's degree or PhD in ... Please note that Meta may leverage artificial intelligence and machine learning technologies in ...

... and adversarial emulation capabilities across the enterprise, cloud, and AI-enabled systems ... Integrate large language models (LLMs) and machine learning capabilities into red team pipelines to ...

Showing results 41-60

Adversarial Machine Learning information

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 Texas? For Adversarial Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Adversarial Machine Learning jobs in Texas look for? The top searched job categories for Adversarial Machine Learning jobs in Texas are:
What cities in Texas are hiring for Adversarial Machine Learning jobs? Cities in Texas with the most Adversarial Machine Learning job openings:
Infographic showing various Adversarial Machine Learning job openings in Texas as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution.

AI & Data Security Engineer

Apple

Austin, TX

$184K - $277K/yr

Full-time

Medical, Dental, Retirement

Re-posted 21 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish.
Apple's Sales organization generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers.
Apple's US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers.
Description
We're looking for an AI & Data Security Engineer responsible for securing data across the full AI lifecycle, from data classification and enforcement of access controls to model deployment and agentic applications. This role designs and enforces row-level security policies, API-driven access controls, and role-based data grants across AI pipelines, chat interfaces, and autonomous agents. Partners closely with Data Governance, Legal, and Engineering to align AI data usage with enterprise policy and regulatory requirements. Leads red team exercises to proactively identify vulnerabilities in AI systems and drives remedial actions. Owns the development of security standards and guidelines that enable product teams to build AI applications securely by default, at scale.","responsibilities":"Design and implement security architecture for AI use cases, ensuring secure data access and usage through role-based access controls and authorized provisioning.
Ensure AI use cases are aligned with Apple’s data classification standards, including appropriate data handling, storage, retention requirements and access controls.
Implement and manage user id and persona based row-level security policies for data stored in Snowflake and other data systems connected to US applications.
Implement and maintain row-level security policies based on user identity and persona across DBX and other data platforms supporting U.S. applications.
Design and implement API-based security controls for AI applications, including authentication, authorization and data access policies to protect sensitive information and ensure compliant data consumption.
Lead adversarial testing of AI systems to identify vulnerabilities, drive remediation, and safeguard Apple data from misuse and malicious activity.
Define and enforce data access boundaries for AI agents, governing permitted data sources, actions and restricting sensitive data access.
Define and enforce data access policies for LLM-powered chat applications, governing usage of structured and unstructured data sources, documents and context that may be surfaced in agentic responses.
Partner with Data Governance, Legal, Privacy and Engineering teams to ensure AI data usage complies with enterprise policies, regulatory requirements (e.g., GDPR, CCPA), and internal data governance standards.
Monitor & Audit AI data access pipelines through logging, anomaly detection and audit trails to detect unauthorized access, data exfiltration attempts or policy violations.
Define and enforce US-wide AI data security standards, best practices, and developer guidelines to implement role-based access controls, enabling secure-by-default data practices at scale.
Preferred Qualifications
AI/ML Security Expertise: Direct experience securing AI/ML lifecycles, LLM-powered applications, or autonomous AI agents (e.g., securing RAG architectures, mitigating prompt injection, defining data access boundaries for AI).
Adversarial Testing: Experience leading or participating in red team exercises, penetration testing, or threat modeling specifically tailored to machine learning models and AI systems.
Cross-Functional Leadership: Demonstrated ability to partner effectively with non-technical stakeholders, including Legal, Privacy, and Data Governance teams, to establish and enforce enterprise wide security standards.
Advanced Threat Detection: Experience building or deploying anomaly detection systems to identify malicious activity within complex data pipelines.
Communication Skills: Strong technical writing skills with a track record of creating developer guidelines, security standards, and best practices that enable secure-by-default engineering at scale.
Education & Certifications: Master's degree in a relevant field, or industry recognized security certifications (e.g., CISSP, CISM, Cloud Security certifications).
Minimum Qualifications
8+ years of professional experience in data security, cybersecurity, security architecture, or data engineering with a primary focus on security.
Data Platform Security: Proven hands-on experience designing and implementing Role-Based Access Control (RBAC), row-level, and column-level security policies in modern cloud data platforms (specifically Snowflake and/or Databricks/DBX).
API & Application Security: Strong expertise in API security controls, authentication, and authorization protocols (e.g., OAuth2, OIDC, SAML, JWT) to protect data access.
Programming Skills: Proficiency in Python, Java, Go, or similar languages used for scripting, automation, and building security controls within data pipelines.
Compliance & Privacy: Solid understanding of data privacy regulations (e.g., GDPR, CCPA) and experience translating these regulatory requirements into technical data governance and access controls.
Monitoring & Auditing: Experience implementing security logging, audit trails, and monitoring solutions to detect unauthorized access or data exfiltration.
Education: Bachelor's degree in Computer Science, Cybersecurity, Information Systems, or equivalent practical experience.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

What Apple employees say

Pay

Benefits

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976