Machine Learning Application Engineer

About the role

The Applied Research Laboratory for Intelligence & Security (ARLIS) at the University of Maryland seeks a Machine Learning Application Engineer to develop, deploy, and sustain end‑to‑end ML solutions that support U.S. national security missions. The role involves translating complex technical problems into robust ML applications, including data preparation, model building, evaluation, and integration into operational workflows.

Key responsibilities

• Design and implement ML pipelines for natural language processing and computer vision tasks.
• Prepare and curate datasets, develop and train models using frameworks such as PyTorch, scikit‑learn, and SciPy.
• Deploy models into production environments using CI/CD practices and workflow orchestration tools.
• Monitor, test, and maintain deployed ML systems to ensure reliability and performance.
• Collaborate with interdisciplinary teams and present technical results to government stakeholders.
• Rapidly prototype research concepts and transition them into usable, interactive applications for end users.

Required profile

• Strong foundation in machine learning concepts and methods.
• Experience translating technical challenges into end‑to‑end ML solutions.
• Ability to work on interdisciplinary teams and communicate technical work effectively.

Required skills

• PyTorch / torch
• scikit‑learn
• SciPy
• CI/CD pipelines
• Workflow orchestration (e.g., Airflow, Kubeflow)
• Monitoring tools for ML systems
• Natural language processing (NLP) techniques
• Computer vision methods and tools