About the position
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, process improvement, software development, data science, and machine learning to deliver responsive, resilient, high-performance software intensive systems to our IC, DoD, and civilian customers. The Data Science and Artificial Intelligence Department (DSAID) seeks a creative and enthusiastic Deep Reinforcement Learning Specialist 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, NOAA, MDA, DHS, etc.). The ideal candidate has deep expertise in Deep Reinforcement Learning, while contributing broadly to AI projects involving one or more of the following: autonomous systems, control and dynamics, robotics, and nonlinear optimization. They are team-oriented, proactive, focused on developing cutting-edge technologies and frameworks, and are comfortable balancing a variety of projects spanning internally funded research and development to direct customer support for mission-critical space systems.
Responsibilities
- Evaluate technologies for use in scalable and resilient mission-critical applications in a production environment
- Champion the deep reinforcement learning and data science bridge between data subject matter experts and customer stakeholders
- Tell stories that describe insights and analytical findings both to engineers and to customer stakeholders
- Build and lead small, innovative teams to develop algorithms and application prototypes
- Fuse together diverse data sources
- Create dynamic data visualizations
- Foster an environment of continual learning
Requirements
- Bachelor's degree in STEM, emphasis Computer Science, Electrical or Computer Engineering, or related field(s)
- Typically, 8 or more years of experience in relevant fields in industry
- Software development skills in at least two different programming languages (e.g., Python, R, C/C++)
- Experience with reinforcement learning libraries in Python
- Experience using deep learning packages (TensorFlow, PyTorch, JAX)
- Experience cleaning data, prototyping, and fine-tuning state of the art deep learning models
- Experience with statistics, machine learning, and reinforcement learning
- Experience with software engineering and software development best practices
- Familiarity with Unix/Linux operating systems
- Demonstrated technical leadership in one or more reinforcement learning projects
- Demonstrated ability to efficiently deliver analysis and insights from data that is large, unstructured, or unprocessed
- Demonstrated ability to operate independently and proactively seek guidance as needed
- Demonstrated ability to communicate technical material to a non-technical audience
- 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
Nice-to-haves
- An advanced degree in Mechanical Engineering, Mathematics, Physics, Electrical Engineering, Computer Science, or related field(s)
- Previous publications in journals/conferences related to machine learning, engineering, or the physical sciences
- Experience with multi-agent reinforcement learning
- Experience with dynamical systems theory, familiarity with concepts and trade-offs associated with stability
- Experience with optimal, robust, and/or nonlinear control
- Demonstrated contributions to open-source software repositories
- Familiarity with containerization technologies (e.g., Docker, Kubernetes, Rancher, etc.)
- Familiarity deploying machine learning models on cloud platforms (e.g., AWS, Azure)
- Experience implementing real-time reinforcement learning algorithms in large scale environments
- Participation in extracurricular activities related to data science (e.g., Kaggle competitions)
- Active security clearance
Benefits
- 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
- An inclusive work environment built on teamwork, flexibility, and respect
