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Machine Learning Defense Jobs in Utah (NOW HIRING)

Mariana Minerals

Extractive Metallurgist

Moab, UT · On-site

$100K - $160K/yr

... defense technologies. We're reimagining the minerals supply chain by combining deep industry ... You'll work closely with operations, engineers, machine learning experts, and data scientists to ...

Prime Machine, Inc.

Welder

Salt Lake City, UT · On-site

$20 - $40/hr

... defense-playing a vital role in keeping the world's infrastructure running. At Prime Machine, our ... Participate in ongoing learning and cross-functional collaboration What We're Looking For: You're ...

Adobe

VP, Cyber Operations

Lehi, UT

This includes security telemetry and advanced capabilities such as data platforms and machine learning that enable scalable, proactive defense. This leaderoperatesat the intersection of strategy ...

Leidos

Cybersecurity Analyst

Sunset, UT

... statistical analysis, and machine learning to detect and respond to advanced threats ... threat defense (MTD). A strong understanding of mobile security best practices and mobile threat ...

Raytheon

Software Engineer II

Provo, UT

$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 ...

Mariana Minerals

Sr. Metallurgical Process Engineer

Moab, UT · On-site

$104K - $135K/yr

... defense technologies. We're reimagining how minerals are sourced, refined, and optimized by ... machine learning teams * Ensure safe operations by supporting EHS, hazard assessments, risk ...

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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 Utah? For Machine Learning Defense jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Machine Learning Defense jobs in Utah look for? The top searched job categories for Machine Learning Defense jobs in Utah are:
What cities in Utah are hiring for Machine Learning Defense jobs? Cities in Utah with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you
Infographic showing various Machine Learning Defense job openings in Utah as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Data Scientist (Artificial Intelligence/Machine Learning)

Data Scientist (Artificial Intelligence/Machine Learning)

U.S. Department of Defense (DOD)

Hill Air Force Base, UT

$125K/yr

Other

Posted 9 days ago

U.S. Department Of Defense rating

7.8

Company rating: 7.8 out of 10

Based on 519 frontline employees who took The Breakroom Quiz

26th of 46 rated military and defense

Job description

See below for important information regarding this job.
Position will be filled at any of the locations listed below. Site specific salary information as follows:
Battle Creek, MI: $125,776- $163,514
Columbus, OH: $131,245- $170,624
Dayton, OH: $130,461 - $169,604
Fort Belvoir, VA: $143,913- $187,093
New Cumberland, PA: $143,913- $187,093
Ogden, UT: $125,776- $163,514
Philadelphia, PA: $138,595- $180,178
Richmond, VA: $131,385- $170,806
Qualifications:To qualify for a Data Scientist (Artificial Intelligence/Machine Learning), your resume and supporting documentation must support:
A. Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
B. Specialized Experience: One year of specialized experience that equipped you with the particular competencies to successfully perform the duties of the position and is directly in or related to this position. To qualify at the GS-14 level, applicants must possess one year of specialized experience equivalent to the GS-13 level or equivalent under other pay systems in the Federal service, military, or private sector. Applicants must meet eligibility requirements including time-in-grade (General Schedule (GS) positions only), time-aftercompetitive appointment, minimum qualifications, and any other regulatory requirements by the cut-off/closing date of the announcement. Creditable specialized experience includes:
  • Conducts large, agency wide, research and development reviews of metrics, measurements, and evaluation methods for emerging and existing areas of Al.
  • Utilizes data science expertise to develop algorithms and tools to support data manipulation and processing as well as the use of data visualization techniques to articulate high risk findings.
  • Ensures the Al systems are designed for auditability to manage Al risk assessment policies and principles which guide automated decisions supporting DLA business operations.
  • Provides expert advice to senior leadership and Al stakeholders to adopt new or revised policy and implementation plans resulting from Al test and evaluation integration.
  • Assesses data quality and establishes standards to validate quality criteria for data to ensure it meets the necessary requirements for Al testing and evaluation.

Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.Education:Are you using your education to qualify? You MUST provide transcripts or other documentation to support your educational claims. Unless otherwise stated: Unofficial transcripts are acceptable at time of application.
GRADUATE EDUCATION: One academic year of graduate education is considered to be the number of credits hours that your graduate school has determined to represent one academic year of full-time study. Such study may have been performed on a full-time or part-time basis. If you cannot obtain your graduate school's definition of one year of graduate study, 18 semester hours (or 27 quarter hours) should be considered as satisfying the requirement for one year of full-time graduate study.
FOREIGN EDUCATION: If you are using education completed in foreign colleges or universities to meet the qualification requirements, you must show that the education credentials have been evaluated by a private organization that specializes in interpretation of foreign education programs and such education has been deemed equivalent to that gained in an accredited U.S. education program; or full credit has been given for the courses at a U.S. accredited college or university.Employment Type: OTHER

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