Intermediate Artificial Intelligence (AI) Engineer

Support a Department of Defense program at MCAS Cherry Point, North Carolina by designing and delivering production-ready AI/ML capabilities.

Responsibilities

• Design, build, test, evaluate, and deploy machine learning models and AI applications to automate tasks and improve business and operational processes
• Build production-ready AI/ML systems using data science and software engineering principles for reliable operation in DoD environments
• Develop and maintain software, scripts, data pipelines, and AI/ML solutions using Python, SQL, and other applicable languages
• Create AI/ML solutions using TensorFlow, PyTorch, or comparable frameworks
• Design, build, configure, and deploy AI applications and supporting infrastructure in cloud environments such as AWS, Microsoft Azure, GCP, or similar platforms
• Design, build, configure, and maintain virtualized and cloud-based systems for data, applications, AI capabilities, and infrastructure
• Support migration and modernization of on-premises applications, data, and systems to cloud-based environments
• Implement automation for cloud infrastructure, data pipelines, AI/ML workflows, deployment processes, and recurring technical activities to improve efficiency, scalability, repeatability, and reliability
• Support DoD cybersecurity, information assurance, and security compliance requirements for AI, cloud, and virtualized environments
• Monitor AI models, applications, systems, and cloud environments to assess performance, scalability, reliability, availability, and operational effectiveness
• Troubleshoot issues across AI/ML applications, cloud environments, data pipelines, interfaces, and deployed systems
• Perform testing, validation, documentation, configuration management, and quality assurance across the AI/ML lifecycle
• Collaborate with data analysts, software developers, cloud engineers, cybersecurity personnel, Government stakeholders, and other technical SMEs to translate operational requirements into technical solutions
• Maintain technical documentation covering system architecture, AI/ML models, cloud configurations, interfaces, deployment procedures, automation, testing, and sustainment

Requirements

• Demonstrated experience designing, building, testing, and deploying machine learning models and AI applications
• Experience integrating data science and software engineering concepts to create production-ready AI systems
• Programming and querying experience with Python and SQL
• Experience using AI/ML frameworks such as TensorFlow, PyTorch, or similar tools
• Experience designing, building, and deploying AI systems in AWS, Azure, GCP, or comparable cloud platforms
• Experience designing, building, and maintaining virtualized and cloud-based environments supporting enterprise data, applications, and infrastructure
• Experience supporting migration of on-premises systems and applications to cloud environments
• Experience automating cloud, infrastructure, data, and AI/ML processes
• Experience supporting cybersecurity and security compliance requirements applicable to AI, cloud, and virtualized environments
• Experience monitoring and optimizing system, model, application, and cloud performance to support scalability, reliability, and operational effectiveness

Technologies

• Python
• SQL
• TensorFlow
• PyTorch
• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform (GCP)

Benefits

• 401(k) matching
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Referral program
• Vision insurance

Preferred Qualifications

• MLOps and AI/ML lifecycle management
• DevSecOps and CI/CD pipelines
• Infrastructure as Code (IaC) and automated cloud provisioning
• Docker, Kubernetes, or other containerization/orchestration technologies
• Cloud-native data storage, processing, and analytics services
• REST APIs and integration of AI/ML capabilities with enterprise applications
• Model versioning, validation, monitoring, retraining, and performance optimization
• Git or comparable source-code/configuration management tools
• DoD cloud environments and cloud security requirements
• Risk Management Framework (RMF), Security Technical Implementation Guides (STIGs), or other DoD cybersecurity requirements
• Working within DoD, Department of the Navy, or U.S. Marine Corps technical environments
• Supporting AI/ML capabilities through development, testing, deployment, operation, and sustainment

Education Requirements

• No degree requires 12 years of general experience
• Associate's degree requires 8 years of general experience
• Bachelor's degree requires 7 years of general experience
• Master's degree requires 6 years of general experience
• Ph.D. requires 4 years of general experience
• Relevant degrees may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, Computer Engineering, Information Technology, Information Systems, or another related technical discipline

Pay

• $110,000.00 - $130,000.00 per year

Security Clearance

• Secret (Required)

Location and Work Setup

• Cherry Point, NC 28533 (Required)
• In person

Minimum experience: 7 years

Education: Bachelor's degree

Location: Cherry Point, NC (onsite)