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Machine Learning Defense Jobs in Gilbert, AZ (NOW HIRING)

Lead AI Engineer

Phoenix, AZ · On-site

$96K - $126K/yr

... based machine learning models. This role focuses on applying artificial intelligence, physics ... HONA), we're launching as an independent, publicly traded aerospace and defense company built on a ...

Coordinate with defensive, engineering, risk, and business stakeholders to ensure engagements are ... Exposure to AI security, LLM testing, AI governance, data security, machine learning workflows, or ...

Controls Technician

Mesa, AZ · On-site

$29.75 - $39.25/hr

Nammo Defense Systems, Inc., a defense contractor, is the primary USA operation of the Nammo Group ... This is a hands-on position which will require constant learning. How you will be rewarded as our ...

Controls Technician

Mesa, AZ · On-site

$29.75 - $39.25/hr

Nammo Defense Systems, Inc., a defense contractor, is the primary USA operation of the Nammo Group ... This is a hands-on position which will require constant learning. How you will be rewarded as our ...

Software Engineer II

Phoenix, 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 ...

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 ...

Software Engineer II

Phoenix, 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

See Gilbert, AZ salary details

$25.4K

$42.4K

$87.7K

How much do machine learning defense jobs pay per year?

As of Sep 13, 2026, the average yearly pay for machine learning defense in Gilbert, AZ is $42,448.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,400.00 and $45,900.00 per year, depending on experience, location, and employer.

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 Gilbert, AZ?

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

What job categories do people searching Machine Learning Defense jobs in Gilbert, AZ look for?

The top searched job categories for Machine Learning Defense jobs in Gilbert, AZ are:

What cities near Gilbert, AZ are hiring for Machine Learning Defense jobs?

Cities near Gilbert, AZ with the most Machine Learning Defense job openings:

Infographic showing various Machine Learning Defense job openings in Gilbert, AZ as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,448 per year, or $20.4 per hour.

Advanced AI Engineer - Mechanical Engineering

Tempe, AZ • On-site

Honeywell International, Inc.
Furniture Manufacturing • 10K+ employees

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago


Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 186 frontline employees who took The Breakroom Quiz


Job description


As an Advanced AI Engineer at Honeywell Aerospace, you will provide technical contributions to the development of AI-driven engineering design tools and physics-based machine learning models. This role focuses on applying artificial intelligence, physics-informed methods, and surrogate modeling to accelerate the design and analysis of aerospace mechanical systems, including wheels and brakes, fuel systems, environmental control systems, and other complex components. You will help shape the next generation of simulation and analysis capabilities by integrating AI with traditional computational tools such as CFD, FEA, and multi-physics solvers.
In this role, you will develop advanced AI surrogates and Physics-AI models, and contribute to the transition these technologies into engineering workflows across Honeywell Aerospace. You will collaborate with cross-functional teams and global research partners, pursue both internal and government research funding, and contribute to the execution from concept through integration. Your work will impact engineering efficiency, product performance, and Honeywell's leadership in AI-enabled engineering design.
Key Responsibilities
  • Contribute to the creation of advanced Physics-AI models and surrogate models to accelerate engineering workflows for CFD, thermal analysis, structural analysis, and system-level simulation.
  • Create scripted FEA or CFD models to generate training data over parameter and load condition spaces.
  • Suggest ideas to drive the AI strategy for engineering design, with a focus on physics-informed neural networks (PINNs), digital twins, and high-fidelity model surrogates.
  • Research and test new AI methodologies for multi-physics modeling of aerospace components such as engines, wheels and brakes, and mechanical actuation systems.
  • Suggest improvements to current processes for efficient data generation, data handling, and model utilization.
  • Utilize and advance state-of-the-art NVIDIA simulation and AI acceleration tools, including Physics NEMO and related model-based AI frameworks.
  • Collaborate closely with engineering teams to integrate surrogate models into design processes, enabling faster trade studies, optimization, and predictive analysis.
  • Contribute to technical execution across internal and government-sponsored R&D projects and contribute to proposal development.
  • Assist with outreach to traditional design and analysis engineering functions.

Qualifications
YOU MUST HAVE
  • Bachelor's degree from an accredited institution in technical disciplines such as the sciences, technology, engineering or mathematics.
  • 2 years of experience developing AI models for physics-based simulation, engineering analysis, multi-physics modeling, or surrogate modeling. Experience in a graduate program may be included.
  • 3 years with simulation scripting (Abaqus Python scripting interface, Ansys PyAnsys or APDL or similar open-source tools).
  • 5 years working on design and simulation of physics of engineering systems involving concepts such as Computational Fluid Dynamics or Structural Analysis
  • Experience mentoring others in specialty areas.
  • Experience with NVIDIA's physics-accelerated AI tools such as Physics NEMO, Modulus, Warp, or similar platforms for physics-informed deep learning

WE VALUE
  • Bachelor's or Master's degree in aerospace engineering, mechanical engineering, or a related engineering discipline.
  • Proficiency in Python and machine learning frameworks such as PyTorch and TensorFlow.
  • Experience with JAX for differentiable models
  • Experience working in structured machine learning deployment environments i.e. MLOps workflows
  • Experience with CFD, structural analysis, thermal modeling, or multi-physics simulation, and the ability to couple these with AI-based surrogates.
  • Experience with AI model architectures used for surrogate modeling, such as but not limited to MeshGraphNets, Neural Operators, Physics-Informed and Physics-Attention models.
  • Experience with model visualization through tools such as PyVista, Matplotlib, Plotly, and others.
  • Awareness of considerations for deploying AI models into engineering design workflows or digital engineering ecosystems.
  • Awareness of current research in physics-informed ML, scientific machine learning, and surrogate modeling at major conferences and journals.

ABOUT HONEYWELL AEROSPACE
Join a company that's reintroducing itself to the aviation community we've helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we're launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution.
Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world's aircraft, your work here has reach, that's rare to find anywhere else.
Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we're shaping what comes next.
Every horizon. Every mission. Every day.
BENEFITS OF WORKING FOR HONEYWELL AEROSPACE
Beyond a performance-driven salary, you'll work alongside dedicated experts on technology that's advancing aviation. As a Honeywell Aerospace employee, you're eligible for a comprehensive benefits package that includes:
  • Employer-subsidized medical, dental, vision and life insurance
  • Short-term and long-term disability coverage
  • 401(k) match, flexible spending accounts and health savings accounts
  • Employee assistance program and educational assistance
  • Parental leave and 12 paid holidays
  • Paid time off for vacation, personal and sick time

Explore your benefits: https://honeywellaerospacebenefits.com/
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Job Posting Date: August 6, 2026
Sponsorship
We are currently not sponsoring applicants for work visas for this position. Applicants must be currently authorized to work in the United States on a full-time basis.
#LI-Hybrid
U.S. PERSON REQUIREMENTS
Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status.

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About Honeywell

Sourced by ZipRecruiter

Honeywell is charging into the Industrial IoT revolution with the establishment of Honeywell Connected Enterprise (HCE), building on our heritage of invention and deep, on-the-ground industry expertise. HCE is the leading industrial disruptor, building and connecting software solutions to streamline and centralize the assets, people and processes that help our customers make smarter, more accurate business decisions. Moving at the speed of software, we are creating, innovating and delivering solutions fast, challenging the way things have always been done, piloting new ways for all of us to work, and expecting our successes to set new standards for our customers and for Honeywell. The Chief Architect for Honeywell Connected Enterprise will lead a team of architects and system engineers responsible for the design of applications and infrastructure that deliver high value outcomes for customers in industrial, buildings, distribution centers, and aerospace vertical markets. The Chief Architect will work directly with leadership, development teams, and offering management to design well integrated solutions that utilize software platforming to encourage reuse and speed to market.

Industry

Furniture manufacturing

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

1906