AI/ML Engineer

About the role

DCCA is a veteran-owned high-technology company specializing in providing information technology services to a variety of government agencies and commercial enterprises since 1982. For over 40 years, DCCA has provided a broad range of IT services, helping clients feel confident in their IT infrastructure and upgrade their technology quickly and efficiently. Internally, DCCA prides itself on a culture built on integrity and inclusivity, allowing employees to build lasting skills and relationships. As a veteran-owned business, DCCA knows the importance of recruiting employees with a wide range of backgrounds, allowing for every problem to be approached by a diverse array of perspectives.

Key Tasks

• Model Deployment & MLOps: Architect, implement, and manage scalable MLOps pipelines for the continuous integration, continuous delivery (CI/CD), and continuous training (CT) of machine learning models within AWS GovCloud environments.
• AI/ML Integration: Seamlessly integrate predictive models, Natural Language Processing (NLP) algorithms, and deep learning neural networks into production microservices and enterprise applications.
• Algorithm Optimization: Optimize machine learning models for performance, latency, and scalability, ensuring they can process large volumes of real-time data efficiently.
• Cybersecurity & Defensive AI: Leverage machine learning for cybersecurity by integrating AI-driven threat detection, fraud prevention algorithms, and defensive cyber operations into system architectures.
• Edge AI & System Sustainment: Design lightweight AI models for Edge AI applications, ensuring high-performance computing capabilities are pushed closer to data sources where required by the mission.
• Infrastructure Management: Utilize cloud-native AI/ML services (e.g., AWS SageMaker) and container orchestration platforms (e.g., Docker, Kubernetes) to provision and scale AI infrastructure dynamically.
• Compliance & Security: Ensure all AI/ML implementations strictly comply with the Risk Management Framework (RMF), NIST 800-53 security controls, and federal guidelines for algorithmic fairness and data privacy.

Required Skills

• Experience: Minimum of 5+ years of hands-on experience in software engineering with a primary focus on deploying and operationalizing AI/ML models.
• Programming Languages: Expert-level proficiency in Python, as well as strong capabilities in Java, C++, or Go.
• Machine Learning Frameworks: Deep technical knowledge of industry-standard AI/ML frameworks such as TensorFlow, PyTorch, Keras, and Scikit-Learn.
• Cloud & MLOps: Proven experience with AWS machine learning services (e.g., SageMaker) and building automated MLOps pipelines using Git, Jenkins, or GitLab CI.
• Clearance: TS/SCI w/Poly

Desired Skills

• Prior experience in engineering AI solutions for federal agencies, including the Department of Defense (DoD), Defense Information Systems Agency (DISA), or the Intelligence Community.
• Familiarity with Cognitive Automation and Robotic Process Automation (RPA) tools.
• Experience with advanced AI disciplines, including Deep Learning for Signal Processing and Electronic Warfare integration.
• Active industry-recognized certifications (e.g., AWS Certified Machine Learning – Specialty, SAFe Agile Certification).

Education

Bachelor's or master's degree in computer science, Artificial Intelligence, Machine Learning, Data Engineering, or a related highly technical discipline.

Benefits

• Healthcare
• Retirement plan
• Paid disability and life insurance programs
• Employee assistance program
• Paid and unpaid leave programs
• Education assistance
• Wellness initiatives
• Annual salary review ensuring pay is equitable across both the company and industry at large
• Upskilling programs and recertification support
• Professional development opportunities
• Business resource groups and other opportunities for connection
• Flexible 401(k) options

Pay

The proposed salary range for this position in Virginia is 195,000 to 259,000. Final salary will be determined based on various factors.