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Adversarial Machine Learning Jobs in Texas (NOW HIRING)

Build, evaluate, and optimize machine learning models through hyperparameter tuning. Implement ... Generative Models-Understanding of GANs (Generative Adversarial Networks), VAEs (Variational ...

SWBC is seeking a talented individual to lead the development of critical machine learning and AI ... adversarial testing, and model performance benchmarking to ensure solution quality before ...

Design and implement machine learning and AI solutions, including predictive models, forecasting ... adversarial testing, and model performance benchmarking to ensure solution quality before ...

Design and implement machine learning and AI solutions, including predictive models, forecasting ... adversarial testing, and model performance benchmarking to ensure solution quality before ...

Design and implement machine learning and AI solutions, including predictive models, forecasting ... adversarial testing, and model performance benchmarking to ensure solution quality before ...

Senior Data Scientist

San Antonio, TX · On-site

$140 - $210/hr

Design and implement machine learning and AI solutions, including predictive models, forecasting ... adversarial testing, and model performance benchmarking to ensure solution quality before ...

... machine learning methodologies to transform cybersecurity data into scalable detection capabilities, enhance analytics, and improve threat detection under complex and adversarial conditions. In this ...

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Familiarity with adversarial ML concepts, such as prompt injection, model inversion, and model ... AI/ML certifications (e.g., Microsoft Azure AI Engineer, AWS ML Specialty, GIAC Machine Learning ...

... adversarial conditions) • Own camera and sensor integration: calibration workflows, intrinsic ... PhD in Computer Vision, Machine Learning, Robotics, or related field • Prior experience ...

... adversarial testing service. We're looking for people who are technically sharp and effective ... Expertise in programming with Python, R, or SQL; hands‑on experience with machine learning ...

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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.

Distinguished Engineer - AI Security

Citizens

Irving, TX • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago


Job description

Description

DISTINGUISHED ENGINEER, AI TOOLING & SECURITY

Why This Role Matters

This role will help define and secure the future of AI at Citizens. The Distinguished Engineer, AI Tooling & Security will shape enterprise engineering practices, accelerate responsible AI adoption, and ensure that AI driven capabilities are developed, deployed, and operated securely at scale while enabling innovation and business growth.

Role Summary

Citizens is seeking a highly accomplished Distinguished Engineer, AI Tooling & Security to drive the design, engineering, and security of AI powered platforms and applications across the enterprise. This role combines deep software engineering expertise with advanced security knowledge to ensure AI solutions are scalable, resilient, secure, and aligned with business objectives.

As a Distinguished Engineer, you will serve as a hands on technical leader and peer mentor, partnering with engineering, architecture, security, data, and business teams to shape the future of AI adoption at Citizens. You will lead the development of innovative solutions, establish engineering standards, influence strategic technology decisions, and advance secure AI capabilities across the organization.

Key Responsibilities

  • Lead the design, development, and implementation of innovative software solutions, platforms, and tools that support enterprise AI initiatives.
  • Collaborate with engineering and architecture teams to define scalable, secure, and maintainable technology solutions aligned with enterprise standards.
  • Build modern, cloud native applications and reusable components that accelerate business outcomes and technology innovation.
  • Incorporate scalability, reliability, performance, observability, and maintainability into distributed systems and platform designs.
  • Champion engineering excellence through code quality, automation, testing, and continuous improvement practices.
  • Serve as a senior technical leader and mentor, fostering a culture of innovation, accountability, and continuous learning.
  • Build and operationalize security controls that protect AI applications, models, agents, prompts, and outputs from misuse and abuse.
  • Secure the full AI and machine learning lifecycle, including data ingestion, model development, training, deployment, monitoring, and runtime operations.
  • Design safeguards against emerging AI threats, including prompt injection, data poisoning, model inversion, adversarial attacks, and unauthorized data exposure.
  • Strengthen identity, authentication, authorization, and access management controls for AI systems, APIs, services, and cloud environments.
  • Secure integrations between AI platforms and enterprise applications, databases, APIs, and SaaS solutions to prevent unauthorized access and data exfiltration.
  • Implement encryption, tokenization, data masking, and privacy preserving controls to protect sensitive information used by AI systems.
  • Develop monitoring, logging, detection, and alerting capabilities to identify anomalous AI behaviors, policy violations, and security threats.
  • Harden cloud platforms, containers, orchestration environments, and infrastructure supporting AI workloads.
  • Evaluate security risks associated with third party AI platforms and services, ensuring appropriate governance and control frameworks.
  • Integrate automated security validation, adversarial testing, and model robustness assessments into engineering and deployment pipelines.
  • Lead technical investigations and response activities related to AI security incidents, model misuse, and data exposure events.
  • Collaborate with architecture, governance, risk, compliance, and engineering teams to align AI security practices with regulatory requirements and business objectives.

Required Qualifications

  • 10+ years of software engineering, platform engineering, security engineering, or data engineering experience.
  • Demonstrated success leading large scale engineering initiatives and influencing technical direction across multiple teams.
  • Strong understanding of AI, machine learning, generative AI, and agentic AI architectures and implementation patterns.
  • Experience developing secure, cloud based applications and services.
  • Strong programming experience in Python and proficiency in at least one additional modern programming language.
  • Experience working with large scale data platforms and analytical workloads.
  • Hands on experience with AWS cloud technologies and securing sensitive workloads.
  • Strong Linux and scripting experience, including Bash.
  • Experience building and maintaining CI/CD pipelines using Jenkins, CircleCI, GitHub Actions, or similar technologies.
  • Deep understanding of application security, cloud security, identity and access management, API security, and secure software development practices.
  • Knowledge of AI security principles, model governance, threat modeling, and secure deployment patterns.
  • Strong understanding of data structures, algorithms, and distributed systems.
  • Excellent communication, collaboration, and stakeholder management skills.
  • Proven ability to mentor and develop engineers while driving technical excellence.

Preferred Qualifications

  • Experience securing enterprise AI, machine learning, or generative AI platforms.
  • Experience within financial services, banking, fintech, or other highly regulated industries.
  • Cloud certifications such as AWS Solutions Architect, AWS Security Specialty, Azure Solutions Architect, or equivalent.
  • Experience with container platforms, Kubernetes, infrastructure as code, and platform engineering practices.
  • Familiarity with emerging AI governance, model risk management, and regulatory frameworks.

Education

  • Required: Bachelor's degree or equivalent combination of education and experience.
  • Preferred: Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Cybersecurity, or a related technical discipline.

Compensation
The salary range for this position is $175,000 to $250,000 per year, plus an opportunity to earn additional incentive earnings. Actual pay is based on various factors including, but not limited to, the budget, work location, and relevant skills and experience.

Benefits
Comprehensive benefits include medical, dental, and vision coverage, retirement plans, parental leave, flexible work arrangements, education reimbursement, wellness programs, and generous paid time off exceeding local requirements.

https://jobs.citizensbank.com/benefits.

Some job boards have started using jobseeker-reported data to estimate salary ranges for roles. If you apply and qualify for this role, a recruiter will discuss accurate pay guidance.

Equal Employment Opportunity

Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.

Education:Why Work for UsEmployment Type: 1ST