Machine Learning Operations (MLOps) Engineer
Core
Design, build, and maintain scalable ML pipelines for training, evaluation, and deployment of machine learning systems for national security applications.
Role type
Mid-level MLOps Engineer
Builds
Robust, secure, and reproducible ML pipelines in mission-critical environments
Domain
National security, artificial intelligence, machine learning
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, Airflow, Kubeflow, Docker, Kubernetes, AWS/Azure/GCP, CI/CD, model versioning, feature stores, GPU clusters
Preferred skills
Deploying ML in regulated environments, data governance, model auditing, distributed training, infrastructure-as-code, national security program support
Technologies
PyTorch, TensorFlow, Airflow, Kubeflow, Docker, Kubernetes, Terraform, CloudFormation
Responsibilities
Design scalable ML pipelines; Operationalize models in secure environments; Implement CI/CD workflows; Manage data pipelines and model versioning; Monitor model performance and drift; Integrate security best practices; Support deployment in classified environments; Contribute to infrastructure design
Seniority
Mid-level, hands-on IC