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Job Description
A Senior Machine Learning Engineer responsible for developing and deploying predictive models within the Condition-Based Maintenance ecosystem to optimize aircraft sustainment and maintenance efficiency for the U.S. Air Force, working at the intersection of aerospace logistics and MLOps.
Key Responsibilities
- Architect and implement advanced predictive models within the Condition-Based Maintenance ecosystem.
- Transition machine learning models from development to production environments.
- Develop operational AI/ML tools to optimize aircraft sustainment and maintenance efficiency for the USAF fleet.
Requirements
- Experience supporting the Air Force Rapid Sustainment Office (RSO) or similar military aerospace logistics environments.
- Proven ability to move advanced predictive models from development into production-grade environments.
- Demonstrated experience in building and deploying operational AI and Machine Learning (ML) capabilities to optimize aircraft sustainment and maintenance efficiency across a fleet.
- Strong understanding of the Condition-Based Maintenance Plus (CBM) ecosystem or similar predictive maintenance systems.
- Experience working at the intersection of high-stakes aerospace logistics and MLOps, including building solutions that are operational tools rather than just theoretical models.
Benefits & Perks
Compensation/salary range not specified
Work schedule not specified
Work environment involves aerospace logistics and cutting-edge MLOps
Equal opportunity employer
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