MLOps Engineer for Secure, Production ML

umd; College Park (MD); On-site; USD 150,000 - 225,000; Full time

Job summary

The University of Maryland's ARLIS invites a mid-level MLOps Engineer to bridge research and production by deploying scalable ML pipelines for national security applications. You will collaborate with AI researchers, software engineers, and domain experts to operationalize models in secure environments.

Responsibilities include CI/CD for ML, data pipelines, model versioning, and monitoring while integrating DevSecOps practices. A U.S. security clearance is required.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
• 3–6 years of experience in software engineering, data engineering, or MLOps.
• Experience with ML frameworks (e.g., PyTorch, TensorFlow) and pipeline tools (e.g., Airflow, Kubeflow).
• Proficiency in Python and experience with containerization (Docker) and orchestration (Kubernetes).
• Experience with cloud platforms (AWS, Azure, or GCP) and ML services.
• Understanding of software engineering best practices (CI/CD, testing, version control).

Responsibilities

• Design, build, and maintain scalable ML pipelines for training, evaluation, and deployment.
• Operationalize machine learning models in secure, production-grade environments (on-prem, cloud, hybrid).
• Implement CI/CD workflows for ML systems, including automated testing, validation, and monitoring.
• Manage data pipelines, feature stores, and model versioning to ensure reproducibility and auditability.
• Monitor model performance, drift, and system health; implement feedback loops and retraining strategies.
• Collaborate with researchers to translate experimental models into production-ready systems.
• Integrate security best practices into ML workflows (DevSecOps for AI systems).
• Support deployment of ML systems in constrained or classified environments.
• Contribute to infrastructure design supporting AI/ML workloads (GPU clusters, distributed systems).

Skills

Python

Data engineering

MLOps

Docker

Kubernetes

PyTorch

TensorFlow

Airflow

Kubeflow

CI/CD

AWS

Azure

GCP

Terraform

CloudFormation

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

Terraform

CloudFormation

Job description

The University of Maryland's ARLIS invites a mid-level MLOps Engineer to bridge research and production by deploying scalable ML pipelines for national security applications. You will collaborate with AI researchers, software engineers, and domain experts to operationalize models in secure environments.

Responsibilities include CI/CD for ML, data pipelines, model versioning, and monitoring while integrating DevSecOps practices. A U.S. security clearance is required.