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Machine Learning Defense Jobs in Arizona (NOW HIRING)

Revolutional, LLC

Data Scientist III

Chandler, AZ

Architect, design, and lead implementation of novel analytic methods and machine learning solutions for cybersecurity defense purposes, including anomaly detection, threat classification, and ...

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What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in deep learning, data science, and software engineering. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses as part of compensation packages.

How much does Lockheed Martin pay AI?

As a Machine Learning Defense professional at Lockheed Martin, salaries typically range from $80,000 to over $130,000 annually, depending on experience, education, and specific role. Compensation may also include benefits such as health insurance, retirement plans, and performance bonuses, with opportunities for career advancement in defense and aerospace sectors.

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 jobs pay $2000 a day?

In the field of Machine Learning Defense, highly specialized roles such as senior machine learning engineers, AI security consultants, or cybersecurity analysts working on AI systems can command daily rates of around $2000 or more, especially with extensive experience, advanced certifications, and working on critical projects. These positions often require expertise in AI algorithms, cybersecurity, and relevant tools like Python, TensorFlow, or cybersecurity frameworks, and may involve consulting or contract work with flexible schedules.

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.

Which 3 jobs will survive AI?

In the field of Machine Learning Defense, roles such as cybersecurity analysts, AI security specialists, and data scientists are likely to persist as they require complex judgment, domain expertise, and ongoing adaptation to evolving threats. These jobs involve critical thinking, understanding of adversarial AI techniques, and specialized skills that are difficult to fully automate. Continuous learning and certifications in cybersecurity or AI are valuable for staying relevant in these roles.

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 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:
What cities in Arizona are hiring for Machine Learning Defense jobs? Cities in Arizona with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you
Infographic showing various Machine Learning Defense job openings in Arizona as of June 2026, with employment types broken down into 2% As Needed, 52% Full Time, and 46% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.
Applied Machine Learning Engineer

Applied Machine Learning Engineer

Infinia Search Inc

Chandler, AZ • On-site

$60 - $95/hr

Contractor

Medical, Dental, Vision

Posted 24 days ago

Job description

Must be a U.S. Citizen
Secret Clearance preferred
This position will to support mission-critical aerospace and defense programs. As an Applied Machine Learning Engineer, you will support informed decision-making around the application of machine learning and AI models in safety- and reliability-constrained systems. This role focuses on evaluating tradeoffs between retrieval-based approaches, fine-tuning, targeted training, and non-ML solutions. The position is onsite in Chandler, AZ and works closely with software, infrastructure, simulation, and GNC engineering teams.

Requirements

· Bachelor’s degree in Computer Science, Engineering, Mathematics, or related STEM field

· 3+ years of applied machine learning experience with production systems

· Demonstrated experience making technical tradeoff decisions around:

· RAG vs fine-tuning vs lightweight adaptation

· Model scope, training data selection, and evaluation

· Strong understanding of model failure modes, overfitting, and distribution shift

· Experience deploying ML in environments where correctness and reliability matter

· Ability to clearly communicate ML risks and limitations to non-ML engineers

· U.S. Citizenship

· Preferred Qualifications

· Experience with simulation, autonomous systems, aerospace, or defense programs

· Exposure to guidance, navigation, or control systems

· Experience working with hybrid ML + classical systems

· Familiarity with regulated or compliance-driven software environments

· Active or prior DoD security clearance

Responsibilities

· Evaluate when machine learning should or should not be applied to engineering problems

· Advise teams on tradeoffs between RAG, fine-tuning, and targeted model training

· Support definition of heuristics for model selection, evaluation, and retraining

· Identify and mitigate ML failure modes in system and simulation contexts

· Collaborate with GNC, software, and infrastructure teams on safe ML integration

Company Description

We’re Infinia Search. We’re a relationship-driven search firm that proves that talent, ambition, curiosity, and an infinite work ethic creates exponential results for our clients and candidates.
Infinia Search logo

About Infinia Search

Sourced by ZipRecruiter

Whether we are recruiting top talent or building out a managed team, Infinia’s focus is developing and strengthening relationships with both clients and candidates, because placing professionals is about more than running web searches and filling empty seats. It’s about the human connection.

Industry

Recruiting and staffing services

Company size

201 - 500 Employees

Headquarters location

Kennett Square, PA, US

Year founded

2016

Social media

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