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The Aerospace Corporation is the trusted partner to the nation's space programs, solving the hardest problems and providing unmatched technical expertise. As the operator of a federally funded research and development center (FFRDC), we are broadly engaged across all aspects of space- delivering innovative solutions that span satellite, launch, ground, and cyber systems for defense, civil and commercial customers. When you join our team, you'll be part of a special collection of problem solvers, thought leaders, and innovators. Join us and take your place in space. At Aerospace, we are committed to providing an inclusive and diverse workplace for all employees to share in our common passion and aspiration - to carry out a mission much bigger than ourselves. Information Systems and Cyber Division (ISCD) staff couple the latest in information system technologies, such as elastic compute clouds, containerization, microservices, real-time operating systems, and visualization frameworks, with expertise in cyber security, software architecture, software engineering, data science, Artificial Intelligence, process improvement, and software development to deliver responsive, resilient, high-performance software intensive systems to our Intelligence Community, DoD, and civilian customers. The Data Science and Artificial Intelligence Department (DSAID) seeks a creative and enthusiastic Machine Learning Engineer to join a diverse team of engineers, data scientists, and programmers with a passion for researching, prototyping, understanding, and building AI and data enabled tools across the space enterprise. We are a growing, innovative, and collaborative department that makes meaningful contributions to National Security Space (AF, NRO, etc.), and Civil and Commercial customers (NASA, MDA, DHS, etc.). This positions specifically is for the Machine Learning Engineering section, where we focus on translating cutting-edge AI research into robust, scalable, and production-ready machine learning solutions. We bridge the gap between theoretical ML solutions and real-world impact by optimizing and scaling ML models, designing and building robust ML software architectures, providing expertise in harnessing the latest advancements in compute hardware, and implementing MLOps and Trusted AI best practices.
