Machine Learning Modeling and Simulation Engineer Security Clearance

Position: Machine Learning Modeling and Simulation Engineer with Security Clearance
Description SAIC is seeking a Machine Learning Modeling and Simulation Engineer in Chantilly, VA. The successful candidate will:
* Develop and maintain physics-based simulation models of spacecraft systems, including structures, sensors, and mission environments.
* Perform end-to-end performance modeling for satellite missions, integrating sensor, orbital, and environmental models.
* Conduct sensor phenomenology studies, including optical, infrared, or radar modeling for detection, tracking, and signature analysis.
* Perform orbital mechanics modeling including orbit determination, orbital maneuvering, and spacecraft flight dynamics.
* Use scripting languages (Python, MATLAB, or similar) to automate workflows, perform data analysis, and interface between simulation tools.
* Apply Artificial Intelligence/Machine Learning (AI/ML) techniques (e.g., supervised/unsupervised learning, reinforcement learning, predictive modeling) to enhance simulation fidelity and performance.
* Develop AI/ML models to analyze and predict satellite system behaviors, performance metrics, and mission outcomes based on simulation data.
* Design and implement algorithms for anomaly detection, predictive maintenance, and optimization of satellite operations.
* Use statistical and machine learning techniques to analyze data, identify patterns, and uncover insights relevant to satellite systems.
* Integrate AI/ML models into existing simulation frameworks and tools to enhance their capabilities. Qualifications
* Bachelor's or Master's degree in Aerospace Engineering, Mechanical Engineering, Physics, or a related field with 5+ years of professional technical experience.
* 3+ years of experience in modeling and simulation for aerospace or space systems.
* Active Top Secret/SCI w/Poly Clearance.
* Strong understanding of sensor phenomenology --such as optical, infrared, or radar systems --and associated modeling methods.
* Intermediate Python programming experience, demonstrated through hands-on experience with tasks such as data manipulation, automation, and development of Python-based solutions.

Experience with libraries such as Num Py, Sci Py, pandas, and matplotlib is beneficial.
* Ability to communicate technical results clearly in written and verbal formats.