AI/ML Engineer

Data Computer Corporation of America•Montgomery, AL

74d•$195,000 - $259,000

About The Position

DCCA is seeking an AI/ML Engineer to deploy and operationalize machine learning solutions, including in AWS GovCloud environments. The role involves architecting and managing scalable MLOps pipelines for continuous integration, delivery, and training; integrating predictive models, NLP algorithms, and deep learning networks into production microservices and enterprise applications; and optimizing models for performance, latency, scalability, and real-time data processing. The engineer will apply machine learning to cybersecurity, including threat detection, fraud prevention, and defensive cyber operations. The role also covers designing lightweight models for Edge AI, managing cloud-native AI/ML infrastructure and container orchestration, and ensuring implementations comply with RMF, NIST 800-53, and federal guidance on algorithmic fairness and data privacy. Candidates must hold an active TS/SCI with Poly clearance.

Requirements

At least 5 years of hands-on software engineering experience, primarily focused on deploying and operationalizing AI/ML models.
Expert-level proficiency in Python.
Strong capabilities in Java, C++, or Go.
Deep technical knowledge of AI/ML frameworks such as TensorFlow, PyTorch, Keras, and Scikit-Learn.
Proven experience with AWS machine learning services such as SageMaker.
Experience building automated MLOps pipelines using Git, Jenkins, or GitLab CI.
Active TS/SCI with Poly clearance.
Bachelor’s or master’s degree in computer science, artificial intelligence, machine learning, data engineering, or a related highly technical discipline.

Nice To Haves

Prior experience engineering AI solutions for federal agencies, including DoD, DISA, or the Intelligence Community.
Familiarity with Cognitive Automation and Robotic Process Automation (RPA) tools.
Experience with deep learning for signal processing and Electronic Warfare integration.
Active industry-recognized certifications, such as AWS Certified Machine Learning – Specialty or SAFe Agile Certification.

Responsibilities

Architect, implement, and manage scalable MLOps pipelines for CI/CD and continuous training of machine learning models in AWS GovCloud.
Integrate predictive models, NLP algorithms, and deep learning neural networks into production microservices and enterprise applications.
Optimize machine learning models for performance, latency, and scalability, including efficient processing of large volumes of real-time data.
Integrate AI-driven threat detection, fraud prevention algorithms, and defensive cyber operations into system architectures.
Design lightweight AI models for Edge AI applications and support high-performance computing closer to data sources when required by the mission.
Use cloud-native AI/ML services such as AWS SageMaker and container orchestration platforms such as Docker and Kubernetes to provision and scale AI infrastructure.
Ensure AI/ML implementations comply with RMF, NIST 800-53 security controls, and federal guidelines for algorithmic fairness and data privacy.