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Machine Learning Modeling and Simulation Engineer
Jobs via Dice, Chantilly, Virginia, United States, 22021
Machine Learning Modeling and Simulation Engineer
Job ID: 2510926
Location: Chantilly, VA, US
Date Posted: 2025-10-21
Category: Engineering and Sciences
Subcategory: Modeling/Sim Engr
Schedule: Full-time
Shift: Day Job
Travel: No
Recruiter: Jobs via Dice
Potential for Remote Work: No
Minimum Clearance Required: TS/SCI with Poly
SAIC is seeking a Machine Learning Modeling and Simulation Engineer in Chantilly, VA.
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 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 NumPy, SciPy, pandas, and matplotlib is beneficial.
Ability to communicate technical results clearly in written and verbal formats.
SAIC is a premier technology integrator providing full life cycle services and solutions in the technical, engineering, intelligence, and enterprise information technology markets. SAIC is Redefining Ingenuity through its deep customer and domain knowledge to enable the delivery of systems engineering and integration offerings for large, complex projects. SAIC's approximately 15,000 employees are driven by integrity and mission focus to serve customers in the U.S. federal government. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $4.5 billion. For more information, visit saic.com.
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Location: Chantilly, VA, US
Date Posted: 2025-10-21
Category: Engineering and Sciences
Subcategory: Modeling/Sim Engr
Schedule: Full-time
Shift: Day Job
Travel: No
Recruiter: Jobs via Dice
Potential for Remote Work: No
Minimum Clearance Required: TS/SCI with Poly
SAIC is seeking a Machine Learning Modeling and Simulation Engineer in Chantilly, VA.
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 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 NumPy, SciPy, pandas, and matplotlib is beneficial.
Ability to communicate technical results clearly in written and verbal formats.
SAIC is a premier technology integrator providing full life cycle services and solutions in the technical, engineering, intelligence, and enterprise information technology markets. SAIC is Redefining Ingenuity through its deep customer and domain knowledge to enable the delivery of systems engineering and integration offerings for large, complex projects. SAIC's approximately 15,000 employees are driven by integrity and mission focus to serve customers in the U.S. federal government. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $4.5 billion. For more information, visit saic.com.
Referrals increase your chances of interviewing at Jobs via Dice by 2x.
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