Intermediate AI Engineer

Jahn Corporation is seeking an Intermediate AI Engineer to help build practical AI/ML models and tools that support aircraft readiness. This is an onsite full-time role in Cherry Point, NC, with a salary of USD 115,000 per year (from $115,000.00 per year) and excellent benefits. A Top Secret (Preferred) clearance is preferred.

What you’ll do

In this role, you will assist in the development of AI/ML models and tools with a focus on predictive maintenance and AI-driven decision support for aircraft readiness. You will work on designing and deploying machine learning pipelines and assessing emerging AI/ML techniques for use in USMC aviation logistics.

• Assist in the development of AI/ML models and tools for aviation logistics use cases.
• Design, develop, train, and validate machine learning models for predictive maintenance using historical aviation data.
• Perform data cleansing, feature extraction, and feature engineering on large-scale datasets to support model development.
• Develop and maintain ML pipelines for model training, evaluation, deployment, and monitoring in production environments.
• Design and develop AI-driven decision support tools to optimize aircraft readiness.
• Evaluate emerging AI/ML techniques and frameworks for applicability to USMC aviation logistics.

What you bring

• 12+ years of specific experience with no degree required (college degree can allow fewer years of experience).
• Experience designing, building, testing, and deploying machine learning models and AI applications to automate tasks and solve complex problems.
• Ability to bridge data science and software engineering concepts to deliver production-ready AI systems.
• Hands-on experience with programming and query languages including Python and SQL.
• Experience with machine learning/AI frameworks such as TensorFlow, PyTorch, or similar tools.
• Experience designing, building, and deploying AI systems and cloud environments using AWS, GCP, Microsoft Azure, or similar platforms.
• Experience designing, building, and maintaining virtualized and cloud-based systems that manage organizational data, applications, and infrastructure.
• Experience supporting migration of on-premises systems to cloud-based environments.
• Experience automating cloud, infrastructure, data, and AI processes to improve efficiency, scalability, and reliability.
• Experience supporting security compliance requirements for AI, cloud, and virtualized environments.
• Experience monitoring system, model, application, and cloud environment performance to ensure scalability, reliability, and operational effectiveness.

Tools and technologies

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