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Generative Adversarial Network Jobs (NOW HIRING)

Orion Innovation

Senior QA Analyst / Tester

... network of member firms, and collaborate with defensive and development teams ... Key accountabilities % of time Accountability * 10 Design and execute comprehensive adversarial ...

OVA.Work

AI Security Engineer

... for adversarial attacks, prompt injection, model abuse, and anomalous behavior. • Implement ... API security • Network security • Application security • Vulnerability assessment • ...

Goldbelt, Inc.

Research Analyst

Washington, DC · On-site

... adversarial propaganda (CAP). Responsibilities Essential Job Functions: * Identify, test and advise ... Conduct network analyses to map to visualize and understands social and bot networks that spread ...

Goldbelt, Inc.

Research Analyst

Washington, DC

... focused on countering adversarial propaganda (CAP). Responsibilities Essential Job Functions ... Conduct network analyses to map to visualize and understands social and bot networks that spread ...

Goldbelt, Inc.

Research Analyst

Washington, DC · On-site

... countering adversarial propaganda (CAP). Responsibilities * Identify, test and advise on the ... Conduct network analyses to map to visualize and understands social and bot networks that spread ...

AnaVation

AI Security & LLM Engineer

Reston, VA

Adversarial Defense : Develop, implement, and maintain advanced input/output guardrails to ... EC-Council Certified Network Defender (CND); GlAC Global Industrial Cyber Security Professional ...

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Generative Adversarial Network information

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How much do generative adversarial network jobs pay per year?

As of Sep 9, 2026, the average yearly pay for generative adversarial network in the United States is $106,570.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $128,000.00 per year, depending on experience, location, and employer.

What is a generative adversarial network?

A Generative Adversarial Network (GAN) is a type of machine learning framework used for generating new data samples that resemble a given dataset. It consists of two neural networks, called the generator and the discriminator, which compete against each other. The generator creates fake data, while the discriminator tries to distinguish between real and fake data. Through this adversarial process, GANs can learn to produce highly realistic images, audio, and other types of data. They are widely used in applications like image synthesis, style transfer, and data augmentation.

What are the key skills and qualifications needed to thrive as a generative adversarial network engineer?

To thrive as a Generative Adversarial Network (GAN) Engineer, you need a solid background in machine learning, deep learning, and mathematics, typically supported by a degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, and experience with GPU computing and model optimization, are crucial technical tools. Strong problem-solving, creativity, and teamwork skills help you develop novel architectures and overcome research challenges. These abilities are essential to drive innovation and create effective, high-performing GAN models in a rapidly evolving AI landscape.

What are typical challenges faced by professionals working with generative adversarial networks in research or industry?

Professionals working with GANs often encounter challenges such as ensuring stable training, preventing mode collapse, and fine-tuning hyperparameters. Training GANs requires balancing the generator and discriminator networks, which can be technically complex and computationally intensive. In a team setting, collaboration with data scientists, machine learning engineers, and domain experts is common to iterate on model architectures and evaluate generated outputs. Additionally, keeping up with rapidly evolving research and tools is essential for ongoing success in this field.

What is the difference between Generative Adversarial Network vs Data Scientist?

AspectGenerative Adversarial NetworkData Scientist
Required credentialsAdvanced knowledge of machine learning, deep learning, programming (Python, TensorFlow)Statistics, programming, data analysis, often a degree in data science or related fields
Work environmentResearch labs, AI development teams, tech companiesBusiness environments, analytics teams, consulting firms
Industry usageAI research, image/video synthesis, data augmentationData analysis, predictive modeling, business insights

While Generative Adversarial Networks focus on creating realistic data through deep learning models, Data Scientists analyze and interpret data to inform business decisions. Both roles require strong technical skills but serve different purposes within the AI and data ecosystem.

What other helpful pages are available for Generative Adversarial Network?

Other pages related to Generative Adversarial Network:

Infographic showing various Generative Adversarial Network job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 11% Part Time, and 6% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $106,570 per year, or $51.2 per hour.

AI Prompt Engineer - Minneapolis, Mn

Minneapolis, MN • On-site

Motion Recruitment
Recruiting and Staffing Services • 501 - 1,000 employees
Learn more about Motion Recruitmentexternal

Contractor

Medical, Dental, Vision, Retirement, PTO

Re-posted 3 days ago

Job description

Job Description

A major enterprise security organization is growing its generative AI research efforts and is looking for an AI Prompt Engineer in Minneapolis. The group is exploring how frontier language models can be incorporated into cybersecurity testing and is building technology that uses AI to uncover weaknesses across software, infrastructure, and network environments.

The position sits at the intersection of AI engineering, cybersecurity, and software development. You will be responsible for designing the instructions and supporting logic that allow large language models to conduct meaningful security analysis. Success in this role requires more than prompt-writing ability; you must understand the security problems being investigated well enough to direct an AI model toward useful findings and distinguish meaningful vulnerabilities from noise.

Required Skills & Experience

  • Proven hands-on work with advanced LLM prompting, prompt engineering, or AI workflow development

  • Strong understanding of cybersecurity fundamentals and how vulnerabilities are identified and exploited

  • Knowledge of malware, network ingress/egress, attack vectors, and common infrastructure weaknesses

  • Programming experience with at least one general-purpose development language

  • Ability to develop structured AI workflows that combine prompts, context, logic, and model responses

  • Experience working with relational, search, or cloud-hosted database technologies

  • Familiarity with PostgreSQL, Elastic/Elasticsearch, Cloud SQL, or equivalent platforms

Desired Skills & Experience

  • Familiarity with automated security testing techniques such as SAST and DAST

  • Security assessment or penetration-testing experience

  • Knowledge of cloud infrastructure and cloud security concepts

  • Exposure to Kubernetes-based environments

  • Experience with Google Kubernetes Engine

  • Previous work involving AI red teaming, model testing, or adversarial AI research

What You Will Be Doing

Daily Responsibilities

  • Design prompt architectures that direct AI models through cybersecurity research and testing tasks

  • Build AI harnesses capable of maintaining relevant context throughout complex security investigations

  • Develop test cases that identify software vulnerabilities and infrastructure exposures

  • Use generative AI to support network-perimeter analysis and discovery of open or risky services

  • Create workflows for identifying suspicious certificate usage and other security-control weaknesses

  • Experiment with different frontier models without being tied to a single provider

  • Assess the usefulness and accuracy of model-generated security findings

  • Partner with engineers responsible for capturing and processing the resulting security data

  • Coordinate with cyber threat hunters who investigate and remediate validated findings

The Offer

  • Contract opportunity

  • Competitive hourly compensation

You will receive the following benefits:

  • Medical Insurance

  • Dental Benefits

  • Vision Benefits

  • Paid Time Off (PTO)

  • 401(k)

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Apply