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AI/ML Engineer with Security Clearance

Ring0 Technologies, Inc.Herndon, VA🇺🇸United States

Why this role stands out

You will drive innovation in national security by developing cutting-edge AI/ML solutions, offering significant career growth within a reputable organization. This role is ideal for a skilled AI/ML Engineer with CNO experience who thrives in a collaborative, mission-focused environment. Apply now to contribute to critical advancements and expand your expertise.

Quick overview

SeniorityMid Senior
Employment typeEmployee
Work modeOn Site
LocationHerndon, VA, United States
Scikit-learnPyTorchTensorFlowMachine Learning

Job description

Ring0 Technologies (“Ring Zero”) is seeking a talented AI/ML Engineer with experience in Computer Network Operations (CNO) to support a long-term mission within Northern Virginia. The candidate should possess strong, hands-on expertise in advanced AI/ML methodologies and have experience with CNO development. You’ll be part of a dynamic team working on next-generation solutions that safeguard national security systems. Responsibilities include but are not limited to: Develop, implement, and optimize AI/ML models to support mission-critical applications.

Apply machine learning techniques to large, complex datasets to enable predictive analytics, anomaly detection, automation, and decision support. Collaborate with CNO development teams; leverage any prior CNO experience to enhance operational tools, workflows, or mission outcomes. Work closely with cross-functional engineering, sponsor, and analytic teams in a secure on-site environment. Document methodologies, model lifecycles, test results, and technical findings. Support long-term research, prototyping, and mission innovation initiatives.

Minimum Qualifications: Active TS//SCI clearance
Demonstrated experience in AI/ML development, including model design, training, evaluation, and deployment.
Strong proficiency in common ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Experience working with large datasets, distributed computing, or GPU-accelerated model training.
Ability to work full-time on-site in Northern Virginia.

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