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Machine Learning Defense Jobs in Minnesota (NOW HIRING)

Galois, Inc.

Principal Scientist

Minneapolis, MN · On-site

... defense, healthcare, semiconductors, and fintech. Life at Galois: People are the foundation of ... Artificial Intelligence, Machine Learning, and Data Science * Software & Systems Analysis

Geologics

Technician III

Maple Grove, MN · On-site

$35/hr

Top Aerospace and Defense company Location: Maple Grove, MN Schedule: 9/80 Education: 2-year ... Understanding basic machining techniques. * Basic understanding of GD&T. If interested in learning ...

Geologics

Technician III

Maple Grove, MN · On-site

$35/hr

Top Aerospace and Defense company Location: Maple Grove, MN Schedule: 9/80 Education: 2-year ... Understanding basic machining techniques. * Basic understanding of GD&T. If interested in learning ...

Geologics

Technician III

Maple Grove, MN · On-site

$35/hr

Top Aerospace and Defense company Location: Maple Grove, MN Schedule: 9/80 Education: 2-year ... Understanding basic machining techniques. * Basic understanding of GD&T. If interested in learning ...

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All JobsMachine Learning Defense JobsMachine Learning Defense Jobs in Minnesota

Machine Learning Defense information

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 Minnesota? For Machine Learning Defense jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Machine Learning Defense jobs in Minnesota look for? The top searched job categories for Machine Learning Defense jobs in Minnesota are:
What cities in Minnesota are hiring for Machine Learning Defense jobs? Cities in Minnesota with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you
Infographic showing various Machine Learning Defense job openings in Minnesota as of June 2026, with employment types broken down into 78% Full Time, and 22% Part Time. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Sr. Aero/Thermal Engineer

NORTH WIND SYSTEMS LLC

Saint Paul, MN • On-site

$100K - $160K/yr

Full-time

Posted 7 days ago

Job description

Summary: The Sr. Aerothermal Engineer for the Digital Twins for Test Systems will lead the design, development, and deployment of real-time digital twins for a large wind tunnel facility complex. We are seeking a dynamic leader with experience fusing modeling and simulation with real-world results to drive the creation of wind tunnel facility digital surrogates to accelerate facility operations and test conduct.

Responsibilities

  • Architect, design, and lead development of real-time wind tunnel facility digital twin / simulation software systems with hardware in the loop
  • Integrate physics-based simulations of the wind tunnel test sections, test articles, and facility mechanical systems with the facility hardware and instrumentation architectures to drive significant improvements in test conduct efficiency, data collection, and anchoring of test facility and test article models
  • Support the test facility software and controls teams to integrate the digital twin capabilities with controls, data acquisition, and data display development efforts
  • Lead a small team of engineers performing digital twin development tasks to align products with broader digital engineering platform development
  • Support the development of techniques with machine learning (ML) and artificial intelligence (AI) for facility data collection and management, digital twin updates, and operational decision making
  • Support integration of configuration management tools with the digital twins to track and manage the test facility baselines
  • Enforce configuration management of all data related to digital twin software and artifacts
  • Prepare clear technical documentation, analysis summaries, charts, and presentations for internal reviews and external stakeholders
  • Interface with customer technical representatives to review and discuss analysis activities and results

Preferred Education / Experience:

  • Advanced degree in Aerospace Engineering, Mechanical Engineering, or a related discipline
  • 5-10 years of experience pertinent to the responsibilities listed above; or
  • A combination of education and experience equivalent to above


Preferred Knowledge / Ability:

  • Demonstrated experience with wind tunnel testing, either in support of facility operations or performing specific test entries
  • Strong competency in the thermodynamic, aerodynamic, and mechanical principles that underpin wind tunnel performance and operations
  • Experience with real time digital twin / simulation software integration environments (e.g., Ansys, Dassault, and Siemens digital twin products)
  • Strong programming skills for modeling and analysis (e.g., Python, MATLAB/Simulink, Fortran, or C++), including scripting for automation of simulations and data reduction
  • Familiarity with supervisory control and data acquisition (SCADA) software and hardware systems
  • Deep understanding of engineering principles, including mechanical, electromechanical, and aerospace systems design, test, and evaluation
  • Proficiency in interpreting engineering plans, technical drawings, and specifications
  • Ability to define complex problems, analyze data, interpret abstract concepts, and develop effective solutions
  • Demonstrated leadership of cross-functional teams from project conception to completion; guiding teams through planning, execution, and delivery phases
  • Skilled in project management, prioritization, budgeting, and delivering results on time
  • Excellent written and verbal communication skills, with the ability to tailor messaging to technical and non-technical audiences
  • Proficient in Microsoft Office and engineering-related software tools
  • Active U.S. security clearance preferred; candidates must be U.S. citizens and eligible to obtain and maintain a clearance

Additional Preferred Qualifications:

  • Experience with aerospace test systems and / or vehicle development programs
  • Background in early-stage research and development, product development methodologies, and innovation strategy
  • Familiarity with Department of Defense (DoD) acquisition processes, R&D funding, and technology development programs