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Machine Learning Defense Jobs in Minnesota (NOW HIRING)

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

Senior Controls Engineer

Shoreview, MN · On-site

$98K - $129K/yr

... learning, and innovation will allow you and your technical work to be noticed fast. From ... systems, defense systems, or other safety-critical machinery is preferred * Experience with ...

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 ...

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 ...

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 ...

Maintenance Internship

Eagan, MN · On-site

$16.50 - $21/hr

... hands-on learning experience in our Maintenance Department. Shifts Available: Open to having ... Actively participate in Food Safety and Food Defense related activities * Perform additional duties ...

Maintenance Internship

Eagan, MN · On-site

$27 - $30/hr

... hands-on learning experience in our Maintenance Department. Shifts Available: Open to having ... Actively participate in Food Safety and Food Defense related activities * Perform additional duties ...

Showing results 21-40

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 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:

Infographic showing various Machine Learning Defense job openings in Minnesota as of June 2026, with employment types broken down into 5% As Needed, 80% Full Time, 12% Part Time, 2% Contract, and 1% Nights. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Principal Scientist

Galois, Inc.

Minneapolis, MN • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 25 days ago


Job description

About Galois

Who We Are: From building digital engineering tools that make space exploration safer to verifying cryptographic libraries that protect some of the world's most valuable data, Galois develops technology to guarantee the trustworthiness of systems where failure is unacceptable.

What We Do: We believe trustworthy systems are built on a formal mathematical foundation. Our researchers apply formal analysis techniques to the design and verification of critical software systems, allowing us to model, analyze, and mathematically prove that a system behaves exactly as intended under all circumstances. With clients including NASA, DARPA, AWS, and the DoW, we leverage our cutting-edge research to deliver high assurance solutions and tools that enhance security, reliability, and operational efficiency across sectors including aerospace & defense, healthcare, semiconductors, and fintech.

Life at Galois: People are the foundation of Galois's success. As an employee-owned company, we care not only about the technologies we develop, but also the path we take to create them. Galois operates under a highly collaborative organizational model that encourages leadership and teamwork and respects the individuals.

For more on our culture and organizational structure, visit Life at Galois.

About This Role

Principal Scientists drive a research agenda and develop R&D opportunities at the intersection of Formal Methods and one or more of our four Research Areas:

  • Rigorous Digital Engineering
  • Artificial Intelligence, Machine Learning, and Data Science
  • Software & Systems Analysis
  • Advanced Cryptography and Privacy

In this role, you will lead externally-funded research programs, engage directly with government and industry clients, and collaborate with multidisciplinary teams to translate your research into deployable solutions that solve real-world challenges. You'll publish and present your findings, mentor junior staff, and help set the national and global agenda for trustworthy systems.

What You'll Bring

  • Formal Methods Experience: Ph.D. (or equivalent) in Computer Science, Applied Mathematics, or a related field, with a track record of high-quality research (publications, patents, or open-source tools) in formal verification, theorem proving, static analysis, or related areas.
  • Domain Mastery: Demonstrated expertise in at least one of our four research areas with evidence of applied projects or publications.
  • Funding & Program Leadership: Proven success securing external research grants or contracts, and managing projects from proposal to delivery.
  • Client Engagement & Communication: Exceptional technical writing and presentation skills; experience translating research outcomes into clear, compelling solutions for government or industry partners.
  • Collaborative Mentorship: A passion for coaching and inspiring technical teams, fostering a culture of creativity, curiosity, innovation, and ownership.

Responsibilities

  • Program Development: Develop and lead an externally funded research program involving frequent client and government agency interactions.
  •  Technical Leadership: Define research roadmaps that integrate formal methods with your domain expertise.
  • Cross-Sector Collaboration: Build partnerships across Galois, academia, government, and industry to advance active research and development programs.
  • Thought Leadership: Publish and speak on your work, establishing a reputation for thought leadership in your domain of expertise.
  • Mentorship: Guide junior engineers and cultivate an inclusive environment where diverse ideas flourish.
Eligibility & Clearance
  • Must be willing to undergo a security investigation and will need to meet eligibility requirements for access to classified information (Active clearance strongly preferred)
  • Must not require a U.S. government export license to authorize access to export-controlled technology and software required to perform this role.
Location

We enjoy a hybrid work environment, and candidates may be based out of any of our offices in Arlington, VA, Dayton, OH, Minneapolis, MN, or Portland, OR. Additionally, being located in Boston, MA is also welcome. 

Benefits

We offer a robust benefits package to provide for your and your family's well-being, including:

  • Employee Stock Ownership Plan (ESOP)
  • 401(k) retirement plan with 5% employer match and immediate vesting
  • Fully paid medical insurance plans and dental and vision reimbursement plan
  • Health Savings Account (HSA) with generous employer contributions
  • Mental health and wellbeing support through our employee assistance program
  • 5 weeks of paid time off and 9 days of paid company holidays each year
  • 16 weeks of fully paid parental leave (available for new parents for birth, adoption, and fostering)
  • 1 week of fully paid "Blue Sky" innovation time each year to pursue your interests

For more information on our benefits, visit Careers at Galois.

Compensation

Compensation is based on the value of your results, not your value as an employee or person. The compensation process, individual salaries, and criteria for salary changes are transparent to the entire company.

For more information about our forward-looking and transparent approach to pay, visit Compensation.

Equal Employment Opportunity

Galois is an Equal Opportunity Employer and does not discriminate in employment opportunities or practices based on race, ethnicity, national origin, ancestry, color, sex, gender identity or expression, sexual orientation, marital or parental status, pregnancy or childbirth, disability, age, religion, creed, genetic information, veteran status, or any other characteristic protected by applicable federal, state, or local law. We encourage and respect different viewpoints and experiences as being essential to the process of innovation. We strive to acquire, grow, and maintain a diverse and inclusive workplace that applies principles and standards equitably while supporting the needs and accommodations of the individual employee.

Consistent with the Americans with Disabilities Act (ADA) and federal and state laws, it is the policy of Galois, Inc. to provide reasonable accommodation when requested by a qualified applicant or employee with a disability, unless such accommodation would cause an undue hardship. If you require reasonable accommodation in completing the employment application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please contact peopleoperations@galois.com