Role overview
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.
What you'll work on
- 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.
What we're looking for
- 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.
Redhorse Corporation is an equal opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected class.
Accommodations:
If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to access job openings or apply for a job on this site as a result of your disability. You can request reasonable accommodations by contacting Talent Acquisition at [email protected]
Redhorse Corporation shall, in its discretion, modify or adjust the position to meet Redhorse’s changing needs.
This job description is not a contract and may be adjusted as deemed appropriate in Redhorse’s sole discretion.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.