AI/ML Engineer, Senior (TS/SCI w/ poly) - Chantilly, VA
About The Position
Noblis is seeking an experienced AI/ML Engineer to support mission-critical national security initiatives. The role involves designing, developing, and deploying advanced machine learning solutions, as well as building the infrastructure needed to operationalize AI capabilities in secure production environments. The position is on-site unless specifically stated otherwise and is based in Chantilly, Virginia. The engineer will develop and containerize ML models, deploy and scale production workloads on Kubernetes, integrate AI/ML capabilities into full-stack applications, and maintain model reliability and performance. The role also includes architecting cloud-native ML infrastructure on AWS; developing DevOps and MLOps pipelines; and deploying and supporting AI/ML systems in secure, classified, high-side environments. The role provides technical leadership by evaluating emerging AI/ML technologies, architecting scalable infrastructure, promoting production-grade practices for security, observability, and governance, and providing technical guidance across engineering teams. The posted salary range is $160,800 to $251,325 per year.
Requirements
- Active Top Secret/SCI clearance with a current polygraph.
- Bachelor’s degree and 8 years of related experience; or master’s degree and 7 years; or associate’s degree and 11 years; or high school diploma/GED and 14 years.
- Production experience deploying ML models, including LLMs.
- Strong proficiency with ML frameworks and containerization, such as PyTorch, Docker, and Kubernetes.
- Full-stack development experience, such as Python and 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.
Responsibilities
- Design, develop, and containerize machine learning models using tools and frameworks such as 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 for model development, testing, deployment, and monitoring.
- Deploy and support AI/ML systems in 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 for evolving AI/ML workloads and mission requirements.
- Establish and promote best practices for production-grade ML systems, including security, observability, and governance.
- Provide technical guidance and thought leadership across AI/ML initiatives and engineering teams.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
