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# Machine Learning Engineer

- **Company:** Mantech International Corporation
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Amazon Web Services, Microsoft Azure, Cloud Computing, R (Programming Language), Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Google Cloud, Keras, Git, SC Clearance, Scikit Learn, Information Technology, Machine Learning Operations, Data Pipelines, Programming Languages
- **Published:** July 7, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9015940/machine-learning-engineer

## About the Role

* Master's degree in Applied Mathematics, Statistics, Computer Science, or related fields.
 * Verifiable work experience defining and implementing data pipelines and machine learning algorithms.
 * Proficiency in Agile Development and Git Operations.
 * Experience creating, maintaining, and communicating complex technical documentation for machine learning systems.

Preferred Qualifications:

 * Experience with the Sponsor's primary cyber risk and compliance automation tools.

Clearance Requirements:

 * An active Secret clearance is required.

Physical Requirements:

 * Must be able to remain in a stationary position 50%.
 * Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
 * Frequently communicates with co-workers, management, and customers, which may involve delivering presentations.
 * Must be able to exchange accurate information in these situations.

## Description

* Collaborate with cross-functional teams-including data scientists, engineers, and architects-to build machine learning models, training tools, and simulation environments that support business functions.
 * Implement the full MLOps lifecycle to deploy, operationalize, scale, and manage automated machine learning models and analytical solutions.
 * Develop and test ML applications according to requirements, running targeted experiments to optimize overall system performance.
 * Train and embed machine learning models into applications using programming languages (Python, Java, R) and core libraries (TensorFlow, Keras, Scikit-learn).
 * Explore and visualize data to uncover key insights and identify specific factors that impact model accuracy and performance.
 * Manage and deploy cloud-based ML services across major cloud computing environments, including AWS, Azure, or Google Cloud Platform (GCP).
 * Follow Agile methodologies to deliver production-ready, highly testable code in small, efficient, and continuous iterations.


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