AI/ML Engineer, Senior (TS/SCI w/ poly) - Chantilly, VA

MSCCN; Chantilly (VA); On-site; USD 161,000 - 251,000; Full time

Job summary

Noblis seeks an experienced AI/ML Engineer to design, develop, and deploy advanced ML solutions for mission-critical national security initiatives. You will operationalize AI capabilities in secure, production environments and lead deployment, observability, and governance across ML systems.

The role requires TS/SCI with polygraph, strong ML/AI and full-stack skills, and experience deploying ML models in AWS and secure environments. This is a demanding, high-impact position in Chantilly, VA.

Qualifications

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

Responsibilities

• Design, develop, and containerize ML models using 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 and JavaScript frontend.
• Ensure model reliability, performance, and maintainability through deployment lifecycles.
• Architect and implement cloud-native ML infrastructure on AWS; develop DevOps/MLOps pipelines.
• Deploy and support AI/ML systems within secure, classified environments.

Skills

Python

JavaScript

ML/AI concepts

DevOps practices

MLOps

Education

Bachelor’s degree in a related field

Master’s degree in a related field

Associate’s degree with related experience

High School diploma

Tools

PyTorch

Ray

Docker

Kubernetes

FastAPI

AWS

Job description

Noblis is seeking an experienced AI/ML Engineer 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.

Posted Salary Range USD $160,800.00 - USD $251,325.00 /Yr.

Job Responsibilities

Model Development & Deployment

• 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.

Infrastructure & Operations

• 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.

Technical Leadership

• 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.

Required Experience

Required Qualifications

• 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

Preferred Experience

Desired Qualifications

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

Certificates/Security Clearances/Other

• Active TS/SCI w/ polygraph