Model-Based Systems Engineer (Mid-Level)

Position Description: Model-Based Systems Engineer (Mid-Level)

Location: Dayton, OH
Clearance Requirement: Must be eligible to obtain and maintain a Top Secret (TS) Security Clearance
Citizenship: U.S. Citizenship Required

Position Overview

MMB Solutions is seeking a mid-level Model-Based Systems Engineer (MBSE) to support the design, development, and integration of advanced distributed systems operating across complex, multi-domain environments. This role involves working within a modern digital engineering ecosystem that enables real-time system modeling, data correlation, and mission-driven decision support across heterogeneous platforms.

The ideal candidate will have a strong foundation in MBSE principles, experience with system architecture development, and the ability to translate operational requirements into executable system models that support analysis, simulation, and lifecycle management.

Key Responsibilities

• Develop, maintain, and manage system models using MBSE methodologies (e.g., SysML, UML)
• Translate stakeholder needs and mission requirements into system architecture and design artifacts
• Support development of digital engineering environments for modeling, simulation, and system validation
• Perform requirements decomposition, traceability, and verification within model-based frameworks
• Integrate models across multiple domains including communications, data processing, and mission systems
• Collaborate with cross-functional engineering teams (software, hardware, RF, and data engineering)
• Support system-of-systems (SoS) analysis and interoperability across distributed platforms
• Contribute to architecture reviews, technical documentation, and design decisions
• Assist in the development of automated workflows for model validation and data integration
• Support lifecycle engineering activities from concept through deployment

Required Qualifications

• 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

Compensation & Benefits

Our goal is to create an environment that rewards hard work while supporting employee well-being and flexibility.

Compensation & Incentives

• Competitive annual salary aligned with experience and market conditions
• Opportunity for performance-based bonuses tied to individual and company success

Health Benefits

• $700/month employer contribution toward health insurance
  OR
• $400/month stipend if you choose to opt out of company-sponsored health coverage

Retirement

• 5% employer matching contribution to 401(k) plans to support long-term financial planning

Life Insurance

• $10,000 employer-provided life insurance coverage

Time Off & Flexibility

• • 200 hours of Paid Time Off (PTO) annually
  • Comp/Flex time available based on project needs and additional hours worked

What Success Looks Like

Success in this role means effectively building and maintaining authoritative system models that:

• Enable informed engineering and operational decisions
• Improve system integration and interoperability
• Support rapid adaptation to evolving mission needs
• Provide a digital representation of complex, distributed system behaviors