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Adversarial Machine Learning Jobs in Alabama (NOW HIRING)

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

Experience training and using Machine Learning models. * Experience using AI observability, tracing, and evaluation tools (e.g., MLflow, Langfuse). * Experience with adversarial testing methods and ...

Experience training and using Machine Learning models. * Experience using AI observability, tracing, and evaluation tools (e.g., MLflow, Langfuse). * Experience with adversarial testing methods and ...

Experience training and using Machine Learning models.Experience using AI observability, tracing, and evaluation tools (e.g., MLflow, Langfuse).Experience with adversarial testing methods and AI red ...

AI Security Engineer

Huntsville, AL · On-site

$120 - $180/hr

Experience training and using Machine Learning models. * Experience using AI observability, tracing, and evaluation tools (e.g., MLflow, Langfuse). * Experience with adversarial testing methods and ...

... against adversarial threats. All tracks require independent research, cross-functional ... Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ...

AI / ML Engineer

Huntsville, AL · On-site

$95 - $150/hr

... against adversarial threats. All tracks require independent research, cross-functional ... Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ...

... against adversarial threats. All tracks require independent research, cross-functional ... Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ...

... against adversarial threats. All tracks require independent research, cross-functional ... Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ...

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Adversarial Machine Learning information

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 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 are popular job titles related to Adversarial Machine Learning jobs in Alabama?

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

What job categories do people searching Adversarial Machine Learning jobs in Alabama look for?

The top searched job categories for Adversarial Machine Learning jobs in Alabama are:

What cities in Alabama are hiring for Adversarial Machine Learning jobs?

Cities in Alabama with the most Adversarial Machine Learning job openings:

Artificial Intelligence / Machine Learning Engineer

DESE Research, Inc.

Huntsville, AL • On-site

$115K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago


Job description

DESE's Cyber Works and Digital Engineering teams design, build, and integrate emerging AI/ML technologies to harden and secure the systems that defend the nation, across ground, missile defense, space, and installation infrastructure S&T programs. We're expanding our Secure AI practice to build and assure trusted, robust AI/ML solutions that interpret complex datasets, predict outcomes, and automate decision-making in support of critical military platforms.This is a consolidated announcement covering multiple tracks; your assignment may emphasize one or a blend of: Classic ML & Predictive Modeling, LLM/GenAI Applications, AI Assurance & Responsible AI, Edge AI/ML Deployment, and hardening AI/ML systems against adversarial threats. All tracks require independent research, cross-functional collaboration, and the ability to clearly communicate complex technical work to stakeholders.Core Responsibilities:Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ensembles, clustering) to modern deep learning architectures.Build LLM-enabled applications and retrieval-augmented generation (RAG) pipelines, including vector embedding generation, vector database integration, and prompt/context engineering.Develop AI assurance and evaluation tooling: robustness testing, bias/fairness analysis, model traceability, red-team/adversarial testing, and audit artifact generation.Optimize and deploy models for production and edge environments (quantization, compression, containerized inference, ONNX/TensorRT).Implement secure model and data pipelines, defend against adversarial ML threats, and ensure supply-chain integrity (SBOM) for AI components.Conduct data processing/analysis to improve model accuracy; document and present development processes and assurance evidence to stakeholders.Contribute to Agile, team-based planning and estimating in a fast-paced, collaborative environment.Minimum Requirements: Bachelor's degree or equivalent experience in CS/CPE/EE/Data Science (or related field).Proven experience in one or more: ML/LLM development, assurance/evaluation tooling, or deploying edge computing solutions.Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.Proficiency in Python and at least one additional language (Java, C++).Strong understanding of data structures, data modeling, and software architecture.Highlighted Skills & Experience: Modern AI: LLM frameworks and application development; vector embeddings and vector databases; RAG architectures; prompt/context engineering; LLM fine-tuning; model evaluation and benchmarking.Classic ML: Feature engineering, model selection/tuning, statistical analysis, and predictive modeling across structured and unstructured data.AI Assurance: Responsible AI practices (robustness, bias/fairness, traceability); adversarial ML defenses; red-team testing; auditability and compliance documentation.Edge & Deployment: ONNX/TensorRT, quantization/compression, ARM/NVIDIA Jetson/DSP targets, containerized inference, MLOps in controlled/classified environments.Platform & DevSecOps: REST APIs, CI/CD for software and ML systems, SAST/DAST, Infrastructure-as-Code, cloud platforms (AWS, Azure, GCP).Domain: Familiarity with computer networking, secure system integration for mission platforms, and test/V&V support (Python/MATLAB analysis).Contributions to open-source AI/ML projects; experience deploying AI models in production, classified, or embedded environments.Understanding of computer security principles and secure software development lifecycle (SSDLC) practices.Why This Role Matters:You'll join a high-impact team solving some of the DoD's hardest problems in AI-enabled system security, building the next generation of trusted, auditable, and mission-ready AI for national defense.About DESEFor the past 43 years, DESE has provided industry-leading technical and engineering solutions in the fields of Defense, Energy, Space, and Environment. As a small, family-oriented business, DESE provides a compelling benefits package including a generous profit-sharing plan, competitive salaries, and perhaps most importantly, the opportunity to work alongside talented professionals leveraging cutting-edge technologies to solve complex and engaging problems.Why employees love working for DESE:At DESE, we are committed to creating a company that is known for its respect and care for employees. We understand that happy employees are what keeps our business going and we strive to provide the best opportunities for each individual working on our team! Here are a few reasons you will love working here:Competitive health, dental and vision insurance with affordable premiumsFlexible work schedulesTwo different flexible spending account optionsCompany paid life insurance with options for employee paid additionalPerformance bonus programEducation reimbursement programCompany paid personal leave for approved philanthropic activitiesVacation, Sick & Holiday leaveRobust 401k profit sharing planOpportunities for internal promotionsEmployee referral incentive programRewards and gifts for service anniversariesDisability Accommodation for Applicants - DESE Research, Inc. is an Equal Employment Opportunity employer and provides reasonable accommodation for qualified individuals with disabilities and disabled veterans in its job application procedures. If you have any difficulty using our online system and you need an accommodation due to a disability, you may use the following alternative email address or phone number to contact us about your interest in employment with us: hrandsecurity@dese.com or 256-837-8004x123.
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