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Generative Ai Cybersecurity Jobs in Reno, NV (NOW HIRING)

Sr AI/ML Engineer

Sparks, NV

$106K - $146K/yr

Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications. * Experience designing and optimizing generative AI models including transformers and ...

Generative Ai Cybersecurity information

See Reno, NV salary details

$56.8K

$132.6K

$185.5K

How much do generative ai cybersecurity jobs pay per year?

As of Jul 26, 2026, the average yearly pay for generative ai cybersecurity in Reno, NV is $132,572.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,700.00 and $149,600.00 per year, depending on experience, location, and employer.

What is the difference between Generative Ai Cybersecurity vs Cybersecurity Analyst?

AspectGenerative Ai CybersecurityCybersecurity Analyst
Required CredentialsCertifications in AI, cybersecurity, and data science (e.g., CISSP, CEH, AI certifications)Certifications like CISSP, CompTIA Security+, CEH
Work EnvironmentFocus on developing AI models, threat detection algorithms, and automation toolsMonitoring security systems, analyzing threats, implementing security measures
Employer & Industry UsageTech companies, cybersecurity firms, organizations deploying AI-driven security solutionsAll industries, including finance, healthcare, government, and private sectors

While Generative Ai Cybersecurity involves creating AI models to enhance security, Cybersecurity Analysts focus on monitoring and responding to threats. Both roles require cybersecurity knowledge, but Generative Ai Cybersecurity emphasizes AI development and automation, whereas Cybersecurity Analysts concentrate on threat analysis and incident response.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or AI cybersecurity specialist, often requiring advanced skills, extensive experience, and relevant certifications. In the context of generative AI cybersecurity, such roles may involve developing secure AI systems, threat detection, and protecting AI infrastructure, with compensation reflecting expertise and responsibility.

Can you make $500,000 a year in cyber security?

Generative AI cybersecurity professionals with advanced skills, certifications, and extensive experience can potentially earn $500,000 or more annually, especially in senior or specialized roles such as security architects or consultants. Achieving this level often requires expertise in AI tools, threat analysis, and leadership in high-demand environments. Compensation varies based on industry, location, and individual qualifications.

How much does generative AI cybersecurity pay?

Generative AI cybersecurity professionals typically earn between $80,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with specialized skills in AI models and security tools can command higher salaries, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Generative AI Cybersecurity Specialist, and why are they important?

To thrive as a Generative AI Cybersecurity Specialist, you need a strong background in cybersecurity principles, AI/ML concepts, and programming (often with degrees in computer science or related fields). Familiarity with cybersecurity tools (like SIEM, IDS/IPS), knowledge of AI frameworks (such as TensorFlow or PyTorch), and relevant certifications (e.g., CISSP, CEH, or AI-specific credentials) are typically required. Analytical thinking, problem-solving, and effective communication are essential soft skills for identifying threats and collaborating across technical teams. These skills and qualifications are critical to protect advanced AI systems from evolving cyber threats and ensure secure deployment of generative AI technologies.

What is Generative AI Cybersecurity?

Generative AI Cybersecurity refers to the use of advanced artificial intelligence models, such as generative adversarial networks (GANs) and large language models, to enhance cybersecurity measures. These AI systems can identify vulnerabilities, simulate cyberattacks, generate realistic phishing attempts for training, and automate threat detection and response. The goal is to proactively strengthen defenses and adapt to evolving cyber threats by leveraging the creative and predictive capabilities of generative AI. This field is rapidly evolving as organizations seek to stay ahead of increasingly sophisticated cyber adversaries.

How does a Generative AI Cybersecurity professional typically collaborate with other teams in an organization?

A Generative AI Cybersecurity professional often works closely with data scientists, software engineers, and IT security teams to identify system vulnerabilities and design AI-driven defenses. Collaboration is essential when developing and deploying AI models that detect threats, as cross-team input ensures that solutions are both technically robust and aligned with organizational security policies. Regular meetings and knowledge-sharing sessions are common, helping to address emerging risks quickly and effectively. This collaborative environment not only strengthens security posture but also offers opportunities for learning and professional growth.

Can generative AI be used in cyber security?

Generative AI is increasingly used in cybersecurity roles to identify vulnerabilities, generate realistic attack simulations, and develop adaptive defense mechanisms. Cybersecurity professionals leverage tools like machine learning models to enhance threat detection and automate response strategies, often requiring knowledge of AI algorithms and security protocols.
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What cities near Reno, NV are hiring for Generative Ai Cybersecurity jobs? Cities near Reno, NV with the most Generative Ai Cybersecurity job openings:
Infographic showing various Generative Ai Cybersecurity job openings in Reno, NV as of June 2026, with employment types broken down into 1% As Needed, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $132,572 per year, or $63.7 per hour.
Sr AI/ML Engineer

$106K - $146K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago


Sierra Nevada Corporation rating

8.7

Company rating: 8.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

17th of 71 rated aerospace companies


Job description

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading the development of complex AI/ML systems, driving innovation, and mentoring team members to deliver impactful solutions. In this role, you will oversee the design, implementation, and deployment of scalable AI/ML models for mission-critical aerospace and defense applications. You will also act as a technical leader, providing strategic guidance on AI/ML initiatives, ensuring compliance with regulatory standards, and collaborating with stakeholders to meet organizational objectives. This position demands advanced technical expertise and the ability to manage high-impact projects in a fast-paced environment.As SNC's corporate team, we provide the company and its business areas with strategic direction and business support spanning executive management, finance and accounting, operations, human resources, legal, IT, information security, facilities, marketing, and communications.

Responsibilities:

  • Exploration & Innovation:
    • Conduct continuous discovery and hypothesis-driven experimentation, rapidly developing prototypes to assess feasibility and potential impact.
    • Partner with business stakeholders to translate non-technical requirements into actionable AI/ML exploration paths.
  • RAG-Focused AI/ML Development:
    • Develop and prototype RAG-based architectures, including embedding pipelines, retrieval strategies, and transformer-based generative components.
    • Explore and validate new approaches for retrieval, indexing, and multimodal document understanding.
    • Apply validation, safety, and explainability practices in support of aerospace/defense requirements.
  • MPC & Real-Time Decisioning Exploration:
    • Design and prototype MPC-aligned models incorporating predictive modeling, optimization, and reinforcement-learning-based control.
    • Develop signal processing, perception, and planning pipelines supporting MPC control loops.
    • Use GPU acceleration, simulation environments, and HPC resources to support MPC experimentation.
  • Advanced AI/ML Modeling & Technical Leadership:
    • Architect, train, and optimize advanced models including transformers, GANs, RL agents, and real-time systems.
    • Provide technical leadership, mentor engineers, and guide cross-functional teams.
  • Safety, Validation & Integration Support:
    • Develop validation and testing frameworks ensuring compliance with safety and reliability standards.
    • Support integration teams with prototypes, documentation, and technical insights as required.

Qualifications You Must Have:

  • Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
  • 10+ years of experience in a related field.
  • Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 12 years of related experience is required.
  • Higher level relevant degree may substitute for experience.
  • Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic). Demonstrated ability to design and optimize generative AI models (e.g., transformers) and neural networks for complex applications.
  • Extensive experience architecting, deploying, and optimizing AI/ML systems, including ANNs, CNNs, and RNNs, in large-scale or mission-critical environments. Led efforts to improve model performance and reliability in production settings.
  • Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.
  • Demonstrated experience leading teams or projects, including mentoring junior staff.
  • Proven track record of deploying AI/ML models in production environments and optimizing them for real-world use cases.
  • Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications.
  • Experience designing and optimizing generative AI models including transformers and GANs.
  • Experience building or integrating transformer-based models for retrieval-augmented or hybrid reasoning systems.
  • Proficiency designing embedding, retrieval, or indexing pipelines for large, multi-source datasets.
  • Familiarity with explainable AI (XAI) techniques for safety-critical environments.
  • Hands-on experience with reinforcement learning and real-time systems applicable to MPC.

Qualifications We Prefer:

  • Master's degree + additional years experience, or Ph.D. in Artificial Intelligence, Machine Learning, or a related field.
  • Experience with hardware acceleration technologies (e.g., CUDA, TensorRT) and high-performance computing systems.
  • Background in autonomous systems, robotics, or sensor fusion.
  • Familiarity with Agile/DevOps methodologies for software development.
  • Certifications in AI/ML or related fields, such as AWS Certified Machine Learning Specialty or Google Professional Machine Learning Engineer.
  • Deep understanding and practical application of Agile/DevOps in large-scale AI/ML projects.
  • Demonstrated experience with reinforcement learning and generative AI models in production or research settings.
  • Advanced proficiency in GPU programming, parallel/distributed computing, and optimizing ML workloads for performance.
  • Expertise in designing and implementing complex ML pipelines, including clustering, dimensionality reduction, generative modeling, and reinforcement learning, aligned to mission objectives and HMI systems.
  • Skilled in analyzing massive, multi-source datasets and delivering end-to-end autonomy software solutions, from requirements to deployment and maintenance.
  • Working knowledge of hardware acceleration technologies (CUDA, TensorRT), edge AI deployments, and explainable AI (XAI) methods.
  • Exposure to or interest in quantum computing for ML applications.

Essential Functions:


  • Contribute to AI/ML innovation and prototyping projects from exploration through technical feasibility assessment.
  • Support cross-functional engineering teams and integration efforts as needed.
  • Travel occasionally (10-20%) to customer sites, test facilities, or conferences.
  • Work in a hybrid office environment, balancing hands-on research with technical leadership.
  • Ensure compliance with safety, regulatory, and cybersecurity standards for AI/ML systems.

This posting will be open for application for a minimum of 5 days and may be extended based on business needs.

Estimated Starting Salary Range: $143,487.14 - $197,294.82. Compensation varies depending on a wide array of factors, such as candidates' key skills, relevant work experience, and education/training/certifications. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled.

SNC offers annual incentive pay based upon performance that is commensurate with the level of the position.

SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.

IMPORTANT NOTICE:

This position requires the ability to obtain and maintain a Secret U.S. Security Clearance. U.S. Citizenship status is required as this position needs an active U.S. Security Clearance for employment. Non-U.S. citizens may not be eligible to obtain a security clearance. The Department of Defense Consolidated Adjudications Facility (DoD CAF), a federal government agency, handles the adjudicative aspects of the security clearance eligibility process for industry applicants. Adjudicative factors which affect the outcome of the eligibility determination include, but are not limited to, allegiance to the U.S., foreign influence, foreign preference, criminal conduct, security violations and illegal drug use.

Learn more about the background check process for Security Clearances.

SNC is a global leader in aerospace and national security committed to moving the American Dream forward. We're known and respected for our mission and execution focus, agility, and disruptive and rapid innovation. We provide leading edge technologies and transformative solutions that support our nation's most critical security needs. If you are mission-focused, thrive in collaborative environments, and want to make our country stronger with state-of-the-art technologies that safeguard freedom, join our team!

SNC is an Equal Opportunity Employer committed to an environment free of discrimination. Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law.


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