Senior ML Engineer
Posted 2026-05-06Redhorse transforms the way government uses data and technology. To support this mission, we are seeking a Machine Learning (ML) Engineer to join our team supporting the Air Force Rapid Sustainment Office (RSO). In this role, you will be a key architect in the Condition-Based Maintenance Plus (CBM+) ecosystem, moving advanced predictive models from development into production-grade environments. Your work ensures that AI/ML capabilities are not just theoretical but are operational tools used to optimize aircraft sustainment and maintenance efficiency across the USAF fleet. This is an opportunity to work at the intersection of high-stakes aerospace logistics and cutting-edge MLOps, building solutions that keep our nation’s aircraft ready for the mission.
Redhorse transforms the way government uses data and technology. To support this mission, we are seeking a Machine Learning (ML) Engineer to join our team supporting the Air Force Rapid Sustainment Office (RSO). In this role, you will be a key architect in the Condition-Based Maintenance Plus (CBM+) ecosystem, moving advanced predictive models from development into production-grade environments. Your work ensures that AI/ML capabilities are not just theoretical but are operational tools used to optimize aircraft sustainment and maintenance efficiency across the USAF fleet. This is an opportunity to work at the intersection of high-stakes aerospace logistics and cutting-edge MLOps, building solutions that keep our nation’s aircraft ready for the mission.
About the Role
Redhorse transforms the way government uses data and technology. To support this mission, we are seeking a Machine Learning (ML) Engineer to join our team supporting the Air Force Rapid Sustainment Office (RSO). In this role, you will be a key architect in the Condition-Based Maintenance Plus (CBM+) ecosystem, moving advanced predictive models from development into production-grade environments. Your work ensures that AI/ML capabilities are not just theoretical but are operational tools used to optimize aircraft sustainment and maintenance efficiency across the USAF fleet. This is an opportunity to work at the intersection of high-stakes aerospace logistics and cutting-edge MLOps, building solutions that keep our nation’s aircraft ready for the mission.
Key Responsibilities
- Architect and maintain production-grade ML pipelines and infrastructure to support program-wide CBM+ initiatives.
- Oversee end-to-end data collection and processing, including the implementation and sustainment of robust ETL pipelines.
- Drive the adoption of MLOps practices to ensure automated model deployment, versioning, and rigorous monitoring.
- Partner closely with data scientists to transition models from experimental stages to production environments efficiently.
- Clean, preprocess, and manage large-scale datasets to ensure high-quality inputs for predictive modeling.
- Perform Exploratory Data Analysis (EDA) and statistical visualization to identify correlations and trends that drive product development.
- Identify and implement opportunities to improve system performance, scalability, and computational efficiency.
- Continuously monitor deployed models for performance drift and degradation, implementing retraining strategies as needed.
- Collaborate within a multi-functional Agile team to align technical tasks with evolving mission objectives.
Required Experience/Clearance
Desired Experience
- Master’s degree in a STEM field, ideally with a focus on Data Science or Artificial Intelligence.
- Advanced understanding of AI/ML applications specifically within predictive maintenance or industrial logistics.
- Hands-on experience with sensor-based failure predictions and time-series modeling.
- Familiarity with Monte-Carlo simulations and the calculation of confidence levels for predictive forecasting.
- Experience working within DoD-specific data environments (e.g., Advana or Jupiter).
- Contributions to open-source ML projects or experience with Git-based collaboration.