USA remote
Senior Ai/ML Engineer
About this role
About the Organization Now is a great time to join Redhorse Corporation. We are a solution-driven company delivering data insights and technology solutions to customers with missions critical to U.S. national interests. We’re looking for thoughtful, skilled professionals who thrive as trusted partners building technology-agnostic solutions and want to apply their talents supporting customers with difficult and important mission sets.
About the Role Redhorse transforms the way government uses data and technology. To support this mission, we are seeking an Artificial Intelligence (AI)/Machine Learning (ML) Engineer to support Condition-Based Maintenance Plus (CBM+) initiatives that improve aircraft sustainment and optimize maintenance and logistics for the United States Air Force (USAF). In this role, you will serve as a key architect in the CBM+ ecosystem, bridging the gap between cutting-edge development and operational deployment.
Working within cross-functional teams in an Agile environment, you will translate complex predictive models into production-grade systems that directly enhance fleet readiness and sustainment efficiency. This is a unique opportunity to operate at the intersection of aerospace logistics and advanced MLOps, delivering high-impact solutions for our nation's defense. Key Responsibilities Lead CBM+ AI/ML initiatives from concept through production deployment, ensuring technical solutions align with mission outcomes, business objectives, and enterprise architecture standards.
Architect and oversee scalable data pipelines, including data ingestion, ETL/ELT processing, feature engineering, data validation, and sustainment of production data workflows. Design, develop, and optimize machine learning, deep learning, and generative AI models to solve complex operational problems and improve predictive maintenance capabilities. Perform advanced exploratory data analysis, statistical modeling, and data visualization to uncover trends, correlations, risk indicators, and actionable insights that guide product and mission decisions.
Build, maintain, and extend knowledge graph capabilities to support semantic reasoning, data integration, and AI-enabled decision support. Provide technical leadership to multi-functional engineering teams, mentoring junior engineers and guiding best practices for model development, MLOps, testing, documentation, and secure deployment. Collaborate with software, data, cloud, and product teams to integrate trained models into production applications, APIs, and operational workflows.