poly) - Chantilly, VA

Military Spouse Corporate Career Network•Chantilly, VA

5d•$160,800 - $251,325•Onsite

About The Position

Noblis is seeking an experienced AI/ML Engineer with Active Top Secret/SCI (TS/SCI) clearance with a current Polygraph to support mission-critical national security initiatives. In this role, you will design, develop, and deploy advanced machine learning solutions while building the infrastructure required to operationalize AI capabilities in secure, production environments.

Requirements

Active Top Secret/SCI (TS/SCI) clearance with a current Polygraph
Bachelor’s degree with 8 years of related experience; OR Master's degree with 7 years of related experience; OR associate’s degree with 11 years of related experience; OR High School diploma/GED with 14 years of related experience
Production experience deploying ML models, including LLMs
Strong proficiency with ML frameworks and containerization (e.g., PyTorch, Docker, Kubernetes)
Full-stack development experience (e.g., Python, JavaScript)
Working knowledge of AWS cloud services
Demonstrated MLOps/DevOps implementation experience
U.S. Citizenship is required

Nice To Haves

AWS Certification, including AWS Certified DevOps Engineer or AWS Certified Solutions Architect Certification

Responsibilities

Design, develop, and containerize machine learning (ML) models using modern frameworks and tools, including PyTorch, Ray, Docker, and FastAPI.
Deploy, manage, and scale production ML workloads on Kubernetes.
Integrate AI/ML capabilities into full-stack applications using Python-based backend services and JavaScript frontend technologies.
Ensure model reliability, performance, and maintainability throughout the deployment lifecycle.
Architect and implement cloud-native ML infrastructure on AWS.
Develop and maintain DevOps and MLOps pipelines to streamline model development, testing, deployment, and monitoring.
Deploy and support AI/ML systems within secure, classified, and high side environments.
Evaluate and adopt state-of-the-art AI/ML models, frameworks, and emerging technologies.
Architect scalable and resilient infrastructure to support evolving AI/ML workloads and mission requirements.
Establish and promote best practices for production-grade machine learning (ML) systems, including security, observability, and governance.
Provide technical guidance and thought leadership across AI/ML initiatives and engineering teams.