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Machine Learning Defense Jobs in Virginia (NOW HIRING)

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site

We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you ... Defense communities. We deliver end-to-end data and technology solutions that advance the ...

NT Concepts

Machine Learning Engineer

Herndon, VA · On-site

We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you ... Defense communities. We deliver end-to-end data and technology solutions that advance the ...

Heven AeroTech

Machine Learning Engineer

Sterling, VA · On-site

Machine Learning Engineer Company: Heven AeroTech Location: Sterling, Virginia FLSA: Exempt About ... Defense/aerospace industry background * Additional Google Cloud certifications * Domain expertise:

Hirekeyz Inc

Sr. Machine Learning Engineer

Fort Belvoir, VA · On-site

$118.20K - $162.30K/yr

Role: Sr. Machine Learning Engineer Location: Ft. Belvoir, VA (On-site with Hybrid Option) Duration ... Defense Cyber Operations (DCO). You will be helping our military defend our cyber security ...

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Machine Learning Defense information

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 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 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 popular job titles related to Machine Learning Defense jobs in Virginia? For Machine Learning Defense jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Machine Learning Defense jobs in Virginia look for? The top searched job categories for Machine Learning Defense jobs in Virginia are:
What cities in Virginia are hiring for Machine Learning Defense jobs? Cities in Virginia with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you
Machine Learning Developer

Machine Learning Developer

Science Applications International Corporation

Arlington, VA • Hybrid

Other

Posted 23 days ago

Job description

SAIC is seeking a talented and experienced Machine Learning Developer to join our dynamic team.

This position is hybrid in Arlington, VA with 2-3 days per week onsite at the Pentagon or the Mark Center.

The ideal candidate will have a strong background in computer science, software engineering, and experience with machine learning algorithms and frameworks. The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI solutions, improve predictive models, and deploy machine learning systems into production.

Key Responsibilities:

  • Develop and implement machine learning models and algorithms to provide suggested values to readiness reports for our DOD client.
  • Refine data collection processes and improve data quality.
  • Design and develop scalable machine learning solutions for various applications.
  • Work with software developers to integrate machine learning models into production systems.
  • Conduct research to identify new approaches and methods for machine learning and AI.
  • Stay updated with the latest trends and advancements in machine learning and AI.
  • Document processes, codes, and workflows for future reference and reproducibility.
  • Provide support and maintenance for deployed machine learning systems. 
SAIC is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

Required Education:

  • Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD and zero (0) years related experience; four (4) years of experience considered in lieu of degree.

Qualifications:

  • Proven experience designing, developing, and deploying OpenAI solutions as a Machine Learning Developer or in a similar role.
  • Strong programming skills in Python, R, C#, Java or similar languages.
  • Experience with deep learning techniques and models.
  • Expertise in natural language processing (NLP) or computer vision.
  • Proficiency with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc.
  • Experience with data preprocessing, data mining, and data visualization techniques.
  • Strong analytical and problem-solving skills.
  • Excellent communication and teamwork abilities.
  • Familiarity with software development best practices and source control (e.g., Git).

Clearance:

  • Active Secret clearance is required for this position.

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