AI/ML Engineer: Production ML in Secure Environments

Noblis, Inc.; Reston (VA); On-site; USD 133,000 - 208,000; Full time

Job summary

Noblis is seeking an experienced AI/ML Engineer to design, develop, and deploy advanced machine learning solutions for mission-critical national security initiatives. You will build infrastructure to operationalize AI in secure, production environments and lead MLOps practices.

Responsibilities include deploying ML models to production, containerizing workflows, and integrating AI into full-stack Python/JavaScript applications, with cloud-native infra on AWS and a strong emphasis on security and

Qualifications

• Active TS/SCI clearance with current Polygraph.
• Bachelor’s degree with 5+ years of related experience; or Master’s with 3+ years; or Associate’s with 8+ years; or HS diploma with 11+ years.
• Experience deploying ML models to production, including LLMs.
• Strong proficiency with ML frameworks and containerization (PyTorch, Docker, Kubernetes).
• Full-stack development experience using Python and JavaScript.
• Working knowledge of AWS cloud services and infrastructure.
• Experience implementing MLOps/DevOps including CI/CD, monitoring, automation.
• U.S. Citizenship is required.

Responsibilities

• Design, develop, and deploy ML models in production.
• Containerize ML models and deploy on Kubernetes.
• Integrate AI/ML with full-stack Python/JavaScript apps.
• Build and maintain cloud-native ML infrastructure on AWS.
• Develop and manage MLOps pipelines for deployment and monitoring.
• Provide technical leadership and guidance across AI/ML initiatives.

Skills

PyTorch

Ray

Docker

Kubernetes

Python

JavaScript

AWS

CI/CD

MLOps

DevOps

Education

Bachelor's degree in related field

Master's degree in related field

Associate's degree

Tools

FastAPI

MLflow

Kubeflow

SageMaker

Job description

Noblis is seeking an experienced AI/ML Engineer to design, develop, and deploy advanced machine learning solutions for mission-critical national security initiatives. You will build infrastructure to operationalize AI in secure, production environments and lead MLOps practices.

Responsibilities include deploying ML models to production, containerizing workflows, and integrating AI into full-stack Python/JavaScript applications, with cloud-native infra on AWS and a strong emphasis on security and