ZipRecruiter

Log In

1

Adversarial Machine Learning Jobs in Washington, DC

IntelliGenesis LLC

Senior AI Engineer

Reston, VA · On-site

$215K - $245K/yr

Experience with adversarial machine learning and AI security * Background in cyber operations or network traffic analysis * Experience deploying models in edge or disconnected environments

IntelliGenesis

Senior AI Engineer

Reston, VA · On-site

$215 - $245/hr

Experience with adversarial machine learning and AI security * Background in cyber operations or network traffic analysis * Experience deploying models in edge or disconnected environments

IntelliGenesis

Senior AI Engineer

Reston, VA · On-site

Experience with adversarial machine learning and AI security * Background in cyber operations or network traffic analysis * Experience deploying models in edge or disconnected environments

IntelliGenesis LLC

Senior AI Engineer

Annapolis, MD · On-site

$175K - $220K/yr

Experience with adversarial machine learning and AI security * Background in cyber operations or network traffic analysis * Experience deploying models in edge or disconnected environments

previous page

Showing results 41-60

All JobsAdversarial Machine Learning JobsAdversarial Machine Learning Jobs in Washington, DC

Adversarial Machine Learning information

See Washington, DC salary details

$16

$24

$29

How much do adversarial machine learning jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for adversarial machine learning in Washington, DC is $24.16, according to ZipRecruiter salary data. Most workers in this role earn between $21.25 and $25.87 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 Washington, DC?

For Adversarial Machine Learning jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Adversarial Machine Learning jobs in Washington, DC look for?

The top searched job categories for Adversarial Machine Learning jobs in Washington, DC are:

Adversarial Machine Learning jobs near you

Artificial Intelligence / Machine Learning Data Engineer

MAG Aerospace

Fairfax, VA

$116K - $140K/yr

Full-time

Re-posted 19 days ago

Job description

MAG Aerospace is staffing for a Artificial Intelligence / Machine Learning Data Engineer.

This position will lead the development of intelligent systems that transform multi-modal sensor data into actionable intelligence for tactical operations. You'll leverage COTS, FOSS/OSS, and custom development to build or integrate everything from edge computer vision to conversational AI assistants, while managing the data pipelines that feed these systems in the most challenging environments. While you'll have a core expertise in either data engineering or model development, you have a passion for mastering the full stack of AI systems.

US Citizens Only

Former US Defense Contractor / US Gov / US Military Experience Only  

This is a Hybrid Position - Remote mainly - but as well on call to come into a MAG office when requested

We are seeking candidates who live in proximity to our corporate HQ in Fairfax, VA primarily but will entertain persons living near our satellite offices in:
Aberdeen, MD - Titusville, FL - Newport News, VA - Carthage NC


Duties include, but not limited to:

Primary Responsibilities:

  • Develop and optimize data-centric AI solutions such as computer vision pipelines for object detection, tracking, and classification
  • Implement advanced AI capabilities including RAG systems, agentic workflows, and fine-tuned LLMs
  • Design and deploy edge-optimized models using TensorRT, ONNX, and quantization techniques
  • Build data engineering pipelines for ETL, feature engineering, and model training
  • Create analytics dashboards and business intelligence solutions for operational insights
  • Implement multi-modal sensor fusion algorithms (visual, thermal, acoustic, RF)
  • Design and maintain data lakes, warehouses, and real-time streaming architectures
  • Develop conversational AI interfaces using open-source LLMs (Llama, Mistral, etc.)
  • Establish and enforce data quality standards, validation checks, and governance procedures throughout the data lifecycle
  • Develop and implement robust testing and validation strategies for AI/ML models, including performance under degraded data conditions, adversarial testing, and operational scenarios
Secondary Responsibilities:
  • Optimize AI workloads for embedded platforms (Jetson, Intel Neural Compute Stick)
  • Implement hardware acceleration using CUDA and TensorRT
  • Profile and optimize memory/power consumption for edge devices
  • Support embedded systems team with AI-specific hardware integration
  • Design distributed inference systems for degraded network conditions

Minimum Requirements:

 

Primary Experience / Qualifications:

  • 5+ years’ experience in machine learning, AI, and data engineering
  • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX)
  • Experience with modern AI paradigms (transformers, diffusion models, neural ODEs)
  • Hands-on experience with LLM deployment and optimization (vLLM, TGI, llama.cpp)
  • Proficiency with data engineering tools (Apache Spark, Airflow, dbt, etc.)
  • Experience with both SQL and NoSQL databases at scale
  • Knowledge of vector databases and embedding systems (Pinecone, Weaviate, pgvector)
  • Experience with computer vision libraries (OpenCV, PIL) and video processing
  • Understanding of MLOps practices and model lifecycle management
Preferred Qualifications
  • Experience with military/defense AI applications
  • Knowledge of agentic AI frameworks (LangChain, AutoGPT, CrewAI)
  • Familiarity with federated learning and edge-cloud hybrid architectures
  • Experience with business intelligence tools (Tableau, PowerBI, Grafana)
  • Knowledge of time-series analysis and anomaly detection
  • Experience with knowledge graphs and semantic reasoning
  • Understanding of explainable AI and model interpretability
  • Experience with MLOps platforms and tools (e.g., MLflow, Kubeflow, Weights & Biases)
  • Published research or patents in relevant areas

Education & Experience:

  • Bachelor's degree in CS, EE, or related field;
  • Master's preferred

Clearance:

  • Must be eligible for Secret security clearance

Other Qualifications:

  • Must be a US citizen

What Makes You Successful Here
  • You can build anything from a computer vision pipeline to a conversational AI assistant
  • You treat data engineering as seriously as model development
  • You understand the tradeoffs between cloud-scale and edge deployment
  • You can explain complex AI concepts to operators and executives alike
  • You see AI as a tool for augmenting human decision-making, not replacing it

Why Join MAG:

  • Work on meaningful problems that directly impact national security
  • Small, elite team where your contributions matter immediately
  • Access to cutting-edge hardware and technologies
  • Rapid prototyping environment - see your ideas deployed in weeks
  • Direct interaction with end users and field deployments
  • Professional development and conference attendance support
  • Flexible work arrangements with occasional field exercises
  • Opportunity to shape the future of tactical edge computing

MAG Aerospace (MAG) is an Equal Opportunity/Affirmative Action Employer and is committed to Diversity and Inclusion. We encourage diverse candidates to apply to our positions.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
Click below for the “EEO is The Law” and “Pay Transparency Nondiscrimination” supplement posters.

https://www.dol.gov/agencies/ofccp/posters

MAG Aerospace (MAG) is committed to providing an online application process that is accessible to all, including individuals with a disability, by offering an alternative way to apply for job openings. This alternative method is available for those who cannot otherwise complete the online application due to a disability or need for accommodation.
MAG provides reasonable accommodation to applicants under the guidance of the Americans with Disabilities Act (ADA), Section 503 of the Rehabilitation Act of 1973, the Vietnam-Era Veterans’ Readjustment Assistance Act of 1974, and certain state and/or local laws.

If you need assistance due to a disability, please contact the MAG Aerospace Recruiting email:
Applicant.Assist@magaero.com or call (703) 376-8993.


Apply