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Machine Learning Defense Jobs in Philadelphia, PA

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Machine Learning Defense information

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$25.7K

$43K

$88.8K

How much do machine learning defense jobs pay per year?

As of Aug 20, 2026, the average yearly pay for machine learning defense in Philadelphia, PA is $42,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,800.00 and $46,400.00 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 Philadelphia, PA?

For Machine Learning Defense jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Defense jobs in Philadelphia, PA look for?

The top searched job categories for Machine Learning Defense jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Machine Learning Defense jobs?

Cities near Philadelphia, PA with the most Machine Learning Defense job openings:

Machine Learning Defense jobs near you

Data Scientist (ARTIFICIAL INTELLIGENCE/MACHINE LEARNING)

U.S. Department of Defense (DOD)

Philadelphia, PA • On-site

$125K/yr

Full-time, Part-time

Posted 14 days ago

U.S. Department Of Defense rating

7.8

Company rating: 7.8 out of 10

Based on 538 frontline employees who took The Breakroom Quiz

28th of 49 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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