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Machine Learning Defense Jobs in Arizona (NOW HIRING)

Rocket Lab

Senior Software Engineer I

Tucson, AZ

$115K - $152K/yr

... defense initiatives. The team has built spacecraft, payloads, and components for missions to the ... Collaborate with researchers on artificial intelligence, machine learning, and computer vision.

Rocket Lab Corporation

Senior Software Engineer I

Tucson, AZ · On-site

$115K - $152K/yr

... defense initiatives. The team has built spacecraft, payloads, and components for missions to the ... Collaborate with researchers on artificial intelligence, machine learning, and computer vision.

Verra Mobility

Senior Cybersecurity Engineer

Mesa, AZ · On-site

$113K - $155K/yr

Implement security solutions that reinforce a defense-in-depth and zero-trust posture. * Contribute ... Knowledge of machine learning for anomaly detection or threat intelligence.

Raytheon

Software Engineer II

Phoenix, AZ

$96K - $132K/yr

Industry experience in defense? Not required -- we'll invest in you. If you meet the minimum ... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ...

Raytheon

Software Engineer II

Tucson, AZ

$92K - $126K/yr

Industry experience in defense? Not required -- we'll invest in you. If you meet the minimum ... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ...

RTX

Software Engineer II with Security Clearance

Tucson, AZ · On-site

$90K - $124K/yr

Industry experience in defense? Not required - we'll invest in you. If you meet the minimum ... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ...

Raytheon

Software Engineer II

Tucson, AZ

$92K - $126K/yr

Industry experience in defense? Not required -- we'll invest in you. If you meet the minimum ... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ...

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Machine Learning Defense information

What is machine learning defense?

Machine learning defense refers to techniques and strategies designed to protect machine learning models from various security threats, such as adversarial attacks, data poisoning, and model theft. These defenses can include methods like adversarial training, input sanitization, and robust model architectures. The goal is to ensure that machine learning systems remain accurate, reliable, and safe even when faced with malicious attempts to manipulate or exploit them. As machine learning becomes more widely adopted, the importance of effective defenses continues to grow.

What are some common challenges faced by professionals in machine learning defense roles, and how can they be addressed?

Professionals in Machine Learning Defense often encounter challenges such as staying ahead of adversarial attacks, managing model robustness, and keeping up with rapidly evolving threat landscapes. Addressing these challenges typically requires continuous learning, collaboration with cybersecurity and data science teams, and implementing rigorous testing and monitoring frameworks for deployed models. Proactively participating in industry forums and staying updated on the latest research also help in identifying emerging threats and mitigation strategies.

What are the key skills and qualifications needed to thrive as a machine learning defense professional, and why are they important?

To thrive as a Machine Learning Defense professional, you need a strong background in computer science, cybersecurity, and machine learning, often supported by degrees in these fields or related certifications. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial machine learning techniques, and knowledge of security protocols are typically required. Critical thinking, problem-solving, and strong communication skills are essential for anticipating threats and collaborating with interdisciplinary teams. These skills ensure that AI systems remain robust and secure against evolving cyber threats, protecting sensitive data and organizational integrity.

What are popular job titles related to Machine Learning Defense jobs in Arizona?

For Machine Learning Defense jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Machine Learning Defense jobs in Arizona look for?

The top searched job categories for Machine Learning Defense jobs in Arizona are:

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Cities in Arizona with the most Machine Learning Defense job openings:

Machine Learning Defense jobs near you

Advanced Analytics Engineer

Rincon Research Corporation

Tucson, AZ • On-site

$101K - $124K/yr

Other

Medical, Dental, Life, Retirement

This job post has expired today. Applications are no longer accepted.

Job description

Why Join Rincon Research Corporation (RRC)?
At Rincon Research Corporation, our primary business is innovating, developing, and fielding digital signal processing (DSP) products and services for the United States Defense and Intelligence Communities in support of national security.
Rincon Research Corporation (RRC), an employee-owned company, is seeking an experienced Analytics Engineer to advance complex intelligence operations and contribute significantly to our analytical capabilities. This position requires solid intelligence and technical expertise, growing leadership skills, and the ability to work independently on challenging intelligence collection and analysis tasks while supporting both fellow analysts and technical staff. The ideal candidate is a talented, tenacious, results-driven individualto work in a multi-disciplinary R&D environment with similarly motivated electrical engineers, mathematicians, computer scientists, and analysts who are collectively responsible for creating custom digital signal processing solutions and leveraging them to make an operational mission impact.
What are the primary responsibilities for the Analytics Engineer II position?
  • Using familiarity with national intelligence databases, sources, methodologies, and analytical tradecraft, extract data relevant to operational and in-development systems
  • Participate as a member of development teams by offering intelligence operator perspective; provide feedback on CONOPs and tool development
  • Working as a member of a team, provide feedback on system efficacy by analyzing results and comparing to optimal/expected system performance; serve as initial validator for new capabilities
  • Collaborate with program managers, engineers, business development, and mission partners to identify analytical requirements and deliver data-driven solutions.
  • Apply artificial intelligence, machine learning, and automation technologies to improve operational efficiency and analytical workflows.
  • Employ newly-developed systems in support of customer mission objectives

What required background will make you successful?
Education:
  • Bachelor Degree in Electrical Engineering, Computer Engineering, Computer Science, Math or related field.

Experience:
  • Minimum 8 years of experience in signals intelligence, electronic warfare, or related technical analysis field

Technical Analysis Skills:
  • Strong data extraction and pattern recognition abilities
  • Experience with statistical analysis and performance metrics evaluation
  • Experience with data analysis, data visualization, and statistical methods using tools such as Python, SQL, R, or similar analytical environments.
  • Working knowledge of artificial intelligence and machine learning concepts, including the application of generative AI, predictive analytics, or automation to mission or business problems.
  • Familiarity with data engineering and DevOps practices, including version control (Git), CI/CD pipelines, containerization (Docker), and cloud-based development environments.

Intelligence Background:
  • Active TS/SCI security clearance
  • Familiarity with Intelligence Community databases and systems
  • Understanding of intelligence collection methodologies and analytical tradecraft standards
  • Knowledge of operational security considerations

Development & Collaboration:
  • Experience in systems testing and validation
  • Proven ability to provide operational feedback to technical development teams
  • Experience with concepts of operations (CONOPS) development
  • Strong understanding of translating operational requirements into technical specifications

Preferred Qualifications:
  • Experience supporting United States Department of Defense and/or the U.S. Intelligence Community.
  • Background in cross-functional team environments, bridging technical and operational perspectives
  • Experience supporting United States Department of Defense and/or the U.S. Intelligence Community.
  • Experience applying AI/ML techniques to ISR, geospatial intelligence, signals intelligence, or mission planning workflows.
  • Familiarity with Agile, DevSecOps, Model-Based Systems Engineering (MBSE), or Digital Engineering practices.
  • Experience with large language models (LLMs), retrieval-augmented generation (RAG), vector databases, or AI agent frameworks.
  • Professional certifications in relevant technical areas

Where is the position located?
This position is located at our Tucson, AZ office
*The likely salary range for this position is $101,000 to $124,000. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.
What benefits does RRC offer?
  • 100% employer-paid premiums for family medical and dental insurance, employee life insurance, short-term and long-term disability (STD & LTD)
  • Flexible reimbursement spending accounts for medical expense and dependent care
  • Immediate participation and vesting in the company's Employee Stock Ownership Plan (ESOP) and 401(k) Plan
  • Employer contributions to RRC's ESOP
  • Employer matching contributions to the company's 401(k) Plan
  • Employer discretionary contributions to the company's 401(k) Plan
Rincon Research Corporation is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.

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