Senior Radar Modeling Simulation Engineer

Chantilly, VA, US • Posted 6 days ago • Updated 15 hours ago
Full Time
On-site
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Job Details

Skills

  • Science
  • Internal Communications
  • Integrated Circuit
  • IC
  • Satellite
  • Digital Signal Processing
  • Scripting
  • MATLAB
  • Workflow
  • Data Analysis
  • Technical Writing
  • Design Review
  • Electrical Engineering
  • Physics
  • Security Clearance
  • Modeling
  • Sensors
  • RF
  • Mathematics
  • Estimating
  • Python
  • NumPy
  • Pandas
  • matplotlib
  • Information Technology
  • Systems Engineering
  • FOCUS

Summary

Job ID: 2611167

Location: Chantilly, VA, US

Date Posted: 2026-04-08

Category: Engineering and Sciences

Subcategory: Systems Engineer

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: TS.SCI_wPoly

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_ON_SITE

Description

SAIC has a funded need for a Senior Radar Modeling Simulation Engineer (Space Systems) to support a rapidly expanding Government Intelligence Community (IC) customer with cutting-edge programs within the National Reconnaissance Office (NRO) in Chantilly, VA.

Note: The role offers a flexible work schedule, but we ask our team to be available for team meetings during core business hours (10:00 a.m. - 3:00 p.m.).

Job Duties to include:
  • Develop and maintain physics-based simulation models of RF systems for spacecraft and space domain awareness.
  • Perform end-to-end performance modeling for satellite missions, integrating sensor, orbital, and environmental models.
  • Conduct radio frequency and radar sensing modeling and digital signal processing of radio frequency data
  • Use scripting languages (Python, MATLAB, or similar) to automate workflows, perform data analysis, and interface between simulation tools.
  • Generate technical documentation, simulation reports, and visualizations to communicate findings and support design decisions.
  • Support trade studies and design reviews by providing modeling insights into performance impacts of design changes.


Qualifications

Required Education and Experience
  • Bachelor's degree in Electrical Engineering, Physics, or a related field with 9+ years of professional technical experience (Master's degree with 7+ years, or PhD with 4+)
  • Active Top Secret/SCI w/Poly Clearance
  • 4+ years of experience in system-level modeling and simulation for radar or communications systems for space vehicles preferred.
  • Experience with high-fidelity modeling of radar systems, ideally with space domain awareness applications
  • Strong understanding of sensor phenomenology for radio frequency and radar systems.
  • Strong mathematics background and experience with control systems and state estimation
  • Intermediate Python programming experience preferred. Experience with libraries such as NumPy, SciPy, pandas, and matplotlib is beneficial.
  • Ability to communicate technical results clearly in written and verbal formats.



Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10111346
  • Position Id: 2611167
  • Posted 6 days ago

Company Info

About SAIC

SAIC® is a premier Fortune 500 mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, civilian and intelligence markets include secure high-end solutions in mission IT, enterprise IT, engineering services and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

We are approximately 24,000 strong; driven by mission, united by purpose, and inspired by opportunities. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.5 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

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