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MMB SolutionsPosted 1 month ago

Model-Based Systems Engineer (Mid-Level)

$110,000–$180,000 year

On-siteDayton, Ohio, United States

Full TimeMid LevelBachelors DegreeSmall

Job Summary

Develop, maintain, and manage system models using MBSE methodologies like SysML and UML to translate stakeholder needs into executable architecture artifacts. Support digital engineering environments for modeling, simulation, and validation while performing requirements decomposition and traceability across communications, data processing, and mission systems. Collaborate with cross-functional teams including software, hardware, RF, and data engineering to integrate models and support system-of-systems analysis. Assist in automated workflow development for model validation and contribute to architecture reviews and lifecycle engineering activities from concept through deployment. Requires Top Secret clearance and 4–8 years of MBSE experience.

Required Qualifications

  • Must be eligible to obtain and maintain a Top Secret (TS) Security Clearance
  • U.S. Citizenship Required
  • Bachelor's degree in Systems Engineering, Electrical Engineering, Computer Engineering, or related technical field
  • 4–8 years of relevant experience in systems engineering with a focus on MBSE
  • Hands-on experience with MBSE tools such as Cameo Systems Modeler, MagicDraw, or similar
  • Strong understanding of SysML and system architecture frameworks (DoDAF, UAF, or similar)
  • Experience with requirements management tools
  • Ability to work in a structured engineering environment with version control and model governance
  • Strong analytical and problem-solving skills
  • Excellent written and verbal communication skills
  • Experience with digital engineering ecosystems and data-driven system environments
  • Familiarity with distributed systems, cloud-based architectures, or containerized platforms
  • Exposure to modeling integrated operational environments involving real-time data ingestion, processing, and visualization
  • Experience with scripting or automation (Python, APIs, etc.) to support model integration

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