Intermediate Artificial Intelligence (AI) Engineer

Intermediate AI Engineer position supporting a Department of Defense program at MCAS Cherry Point in Cherry Point, North Carolina (onsite).

Responsibilities

• Design, build, test, evaluate, and deploy machine learning models and AI applications that automate tasks, improve business and operational processes, and solve complex technical problems
• Apply data science and software engineering principles to deliver production-ready AI/ML systems that operate reliably in DoD environments
• Develop and maintain software, scripts, data pipelines, and AI/ML solutions using Python, SQL, and other applicable programming and query languages
• Create AI/ML solutions using frameworks and libraries such as TensorFlow, PyTorch, or comparable technologies
• Design, build, configure, and deploy AI applications and supporting infrastructure in cloud environments including AWS, Microsoft Azure, Google Cloud Platform (GCP), or similar platforms
• Design, build, configure, and maintain virtualized and cloud-based systems supporting organizational 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 activities across the AI/ML development and deployment lifecycle
• Collaborate with data analysts, software developers, cloud engineers, cybersecurity personnel, Government stakeholders, and other technical SMEs to convert operational requirements into technical solutions
• Produce and 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 build 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 on AWS, Azure, GCP, or comparable cloud platforms
• Experience designing, building, and maintaining virtualized and cloud-based environments for 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 for AI, cloud, and virtualized environments
• Experience monitoring and optimizing performance for systems, models, applications, and cloud to support scalability, reliability, and operational effectiveness

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
• Experience working within DoD, Department of the Navy, or U.S. Marine Corps technical environments
• Experience supporting AI/ML capabilities through development, testing, deployment, operation, and sustainment

Required Education and Experience

• Bachelor's degree + 7 years of general experience
• Relevant degree areas may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, Computer Engineering, Information Technology, Information Systems, or another related technical discipline
• Experience equivalencies: Associate's degree (8 years), Master's degree (6 years), Ph.D. (4 years), with degree options mapped to general experience requirements

Technologies

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

Compensation

• $110,000.00 - $130,000.00 per year

Security Clearance

• Secret (Required)

Work Location

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

Benefits

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