The Aerospace Corporation-posted 3 days ago
Full-time • Mid Level
Onsite • Chantilly, VA
1,001-5,000 employees

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. 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 position 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. This is a full-time position based in Chantilly, VA which requires 100% onsite work. What You’ll Be Doing DSAID’s customers range from National Security Space (AF, NRO, etc.) to civil (NASA, NOAA, etc.) and commercial (commercial space, autonomous vehicles, etc.) DSAID applies data science and AI knowledge across the space enterprise, to Aerospace enterprise capabilities, and towards corporate workforce development and strategic focus areas Machine Learning Engineers learn and develop their skills by working on teams spanning disciplines, experience levels, and organizational boundaries. Duties, responsibilities and activities may change, or new ones may be assigned as needed Machine learning engineers must maintain a commitment to ongoing learning in order to stay current with government missions and the ever-changing climate of data science and AI. This requires both ongoing education in relevant domains, such as physics, math, and/or computer science, as well as an understanding of the existing systems and future objectives of government missions.

  • Evaluation of technologies for use in scalable and resilient mission-critical applications in a production environment
  • Coordinated development and execution of AI/ML experiments
  • Coordinated development of proof-of-concept infrastructure configuration and software prototypes
  • Collaboration with small, innovative teams to deliver features and products
  • Written and verbal presentation of results to team members and stakeholders
  • Reinforcing an environment of learning and progress with team members and others
  • Focus on accountability and innovation in leadership competency development
  • Bachelors or Master’s degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering or related technical field(s)
  • 5 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain
  • Strong proficiency in at least two different programming languages (e.g. Python, R, C/C++), and ML frameworks including familiarity with machine learning and deep learning libraries in Python
  • Hands on experience with container orchestration tooling(Docker, Kubernetes, etc.)
  • Experience with and understanding of software engineering concepts with an AI focus (MLOps/DevOps, ML Development Lifecycle, data structures, etc.)
  • Working knowledge of Unix/Linux operating systems
  • This position requires ability to obtain and maintain a security clearance, which is issued by the US government.
  • U.S citizenship is required to obtain a security clearance.
  • 8 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain
  • Demonstrated experience architecting, designing, or implementing enterprise-scale AI/ML solutions with multiple tenants and cloud integration
  • Hands on Experience with MLOps and Data Engineering tools (e.g., MLFlow, Kubeflow, Neptune, Airflow, DVC)
  • Advanced degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering, or related field(s)
  • Experience in designing or managing enterprise-level ML platforms and production-grade ML models at scale
  • Familiarity with High Performance Computing hardware for ML (GPUs, TPUs), CUDA programming, and advanced ML optimization techniques and architectures
  • Demonstrated ability to exercise judgement and critical thinking in a scientific discipline
  • Experience implementing and guiding teams toward software development best practices
  • Experience in SQL, NoSQL, Cypher and other big data querying languages
  • Experience with big data frameworks (Hadoop, Spark, Flink etc.)
  • Familiarity with data pipelining and streaming technologies (Apache Kafka, temporal, etc.)
  • Demonstrated contributions to open-source software repositories (github, kaggle, etc.)
  • Experience deploying ML models on cloud platforms (AWS, Azure, etc.)
  • Domain expertise relevant to one or more customer organization mission areas (USSF, NRO, etc.)
  • Comprehensive health care and wellness plans
  • Paid holidays, sick time, and vacation
  • Standard and alternate work schedules, including telework options
  • 401(k) Plan — Employees receive a total company-paid benefit of 8%, 10%, or 12% of eligible compensation based on years of service and matching contributions; employees are immediately eligible and vested in the plan upon hire
  • Flexible spending accounts
  • Variable pay program for exceptional contributions
  • Relocation assistance
  • Professional growth and development programs to help advance your career
  • Education assistance programs
  • A work environment built on teamwork, flexibility, and respect
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