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# Air Force A10 AI/ML Engineer / Data Scientist

- **Company:** Noblis Inc.
- **Location:** Arlington, VA, United States
- **Salary:** $207,750.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Data Fusion, DevOps, Python (Programming Language), Machine Learning, Cloud Services, Tensorflow, Pytorch, Large Language Models, Deep Learning, Fastapi, Containerization, Kubernetes, Machine Learning Operations, Docker
- **Published:** July 18, 2026
- **Apply:** https://dejobs.org/x/x/BCE4215745FD4478936E36571BBA6C42/job/

## About the Role

* Bachelor's degree and 5 years of experience. In lieu of a degree will also consider an Associates & 8 years of experience, or HS & 11 years of 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
 * Must be a US Citizen with a Top Secret Clearance & SCI eligibility

Desired Qualifications

 * Experience with Defense systems data fusion, permissions, Authority to Operate requirements, and deployment on Government systems.

## Description

_This is part of a proposal effort and is contingent on contract award_**

Noblis is hiring multiple AI/ML Engineers and Data Scientists. This will be a full-time role located onsite at a Government facility in the National Capital Region (NCR). 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.

Additionally, the Analyst shall provide the following support:

 * 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.
 * Integrate AI/ML capabilities into full-stack applications.
 * 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.


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