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Adversarial Machine Learning Jobs in Plano, TX (NOW HIRING)

PB consulting

Generative AI Engineer

Colleyville, TX · On-site

Develop and optimize machine learning, deep learning, and NLP models for enterprise applications ... and Generative Adversarial Networks (GANs). * Experience with data preprocessing, feature ...

Pwc

AI Engineer

Fort Worth, TX · On-site

$50K - $112K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output ...

Pwc

AI Engineer

Dallas, TX · On-site

$50K - $112K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output ...

Citizens

Distinguished Engineer - AI Security

Irving, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Secure the full AI and machine learning lifecycle, including data ingestion, model development ... Integrate automated security validation, adversarial testing, and model robustness assessments into ...

Citizens

Distinguished Engineer - AI Security

Irving, TX

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Secure the full AI and machine learning lifecycle, including data ingestion, model development ... Integrate automated security validation, adversarial testing, and model robustness assessments into ...

Citizens

Distinguished Engineer - AI Security

Irving, TX

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Secure the full AI and machine learning lifecycle, including data ingestion, model development ... Integrate automated security validation, adversarial testing, and model robustness assessments into ...

Citizens

Distinguished Engineer - AI Security

Irving, TX

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Secure the full AI and machine learning lifecycle, including data ingestion, model development ... Integrate automated security validation, adversarial testing, and model robustness assessments into ...

AT&T

Senior Data Scientist

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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

GM Financial

Cybersecurity AI_ML Engineer

Irving, TX · On-site

  • Retirement

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

HiddenLayer

Enterprise Account Director- TOLA

Dallas, TX · On-site +1

HiddenLayer protects the world's most valuable technologies from adversarial AI attacks. We were ... Deep understanding of AI security concepts, including machine learning, threat detection, anomaly ...

Hidden Layer

Enterprise Account Director- TOLA

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

HiddenLayer protects the world's most valuable technologies from adversarial AI attacks. We were ... Deep understanding of AI security concepts, including machine learning, threat detection, anomaly ...

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Showing results 21-40

All JobsAdversarial Machine Learning JobsAdversarial Machine Learning Jobs in Plano, TX

Adversarial Machine Learning information

See Plano, TX salary details

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How much do adversarial machine learning jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for adversarial machine learning in Plano, TX is $20.41, according to ZipRecruiter salary data. Most workers in this role earn between $17.93 and $21.88 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.

What are popular job titles related to Adversarial Machine Learning jobs in Plano, TX?

For Adversarial Machine Learning jobs in Plano, TX, the most frequently searched job titles are:

What job categories do people searching Adversarial Machine Learning jobs in Plano, TX look for?

The top searched job categories for Adversarial Machine Learning jobs in Plano, TX are:

What cities near Plano, TX are hiring for Adversarial Machine Learning jobs?

Cities near Plano, TX with the most Adversarial Machine Learning job openings:

Adversarial Machine Learning jobs near you
Infographic showing various Adversarial Machine Learning job openings in Plano, TX as of August 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 100% In-person job distribution, with an average salary of $42,459 per year, or $20.4 per hour.

Generative AI Engineer

PB consulting

Colleyville, TX • On-site

Full-time

Posted 14 days ago

Job description

We are seeking a skilled Generative AI Engineer to design, develop, and deploy advanced AI solutions that solve complex business challenges. The ideal candidate will have strong expertise in Python, Large Language Models (LLMs), machine learning, deep learning, and Natural Language Processing (NLP), with hands-on experience building and optimizing generative AI applications using open-source models and modern AI frameworks.

Roles and Responsibilities

  • Design, develop, and implement advanced AI and Generative AI solutions to address complex business requirements.

  • Collaborate with engineers, researchers, product managers, and business stakeholders to translate business needs into scalable AI solutions.

  • Collect, clean, prepare, and engineer data for training, fine-tuning, and evaluating AI models while ensuring data quality and integrity.

  • Develop and optimize machine learning, deep learning, and NLP models for enterprise applications.

  • Build and deploy Generative AI solutions using Large Language Models (LLMs), text generation, and text-to-image generation techniques.

  • Evaluate, compare, and optimize AI model architectures, hyperparameters, and performance metrics.

  • Apply responsible AI practices by identifying model bias, improving fairness, and ensuring ethical AI development.

  • Develop scalable AI solutions that integrate with enterprise applications and cloud platforms.

  • Participate in model testing, deployment, monitoring, and continuous improvement.

  • Contribute to AI best practices, technical documentation, and knowledge sharing across teams.

Required Skills

  • Strong proficiency in Python with major machine learning and deep learning libraries.

  • Hands-on experience with open-source Large Language Models (LLMs) such as Llama, Dolly, or similar models.

  • Strong knowledge of Machine Learning, Deep Learning, Natural Language Processing (NLP), neural networks, transformers, supervised and unsupervised learning.

  • Experience with Generative AI techniques including text generation, text-to-image generation, and Generative Adversarial Networks (GANs).

  • Experience with data preprocessing, feature engineering, SQL, and data manipulation.

  • Familiarity with AI model evaluation, optimization, and hyperparameter tuning.

  • Strong analytical, problem-solving, and communication skills.

Preferred Skills

  • Experience with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP).

  • Experience developing AI applications in both on-premises and cloud environments.

  • Knowledge of CI/CD pipelines and AI application deployment practices.

  • Familiarity with MLOps, model lifecycle management, and scalable AI deployment architectures.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

  • Experience designing, developing, and deploying enterprise AI or Generative AI solutions.

  • Ability to work effectively in cross-functional teams and deliver high-quality AI solutions in an agile environment.

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