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Internship Control Theory Engineer Jobs in Virginia

MAG Aerospace

$80 - $120/hr

Understanding of control theory and path planning algorithms * Experience with hardware ... You apply systems engineering rigor to rapid prototyping * You're comfortable with both lab ...

CloudFit Software

Command & Control Engineer

Lynchburg, VA · On-site

$16.83 - $21.63/hr

CloudFit Command and Control Engineers (CCEs) protect our customers' interests 24x7x365 as they ... roles, benefits, internships, and more! About This Opportunity This role may be part of our ...

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Internship Control Theory Engineer information

What does an internship control theory engineer do?

An Internship Control Theory Engineer works alongside experienced engineers to design, analyze, and implement control systems for various applications, such as robotics, automation, or aerospace. Interns typically assist in modeling dynamic systems, developing algorithms, running simulations, and supporting experimental validation. This role offers hands-on experience with industry tools and exposure to real-world engineering challenges while applying theoretical knowledge from coursework.

What are the key skills and qualifications needed to thrive as an internship control theory engineer?

To thrive as an Internship Control Theory Engineer, a solid background in mathematics, dynamics, and control systems, typically supported by coursework in engineering or applied mathematics, is essential. Familiarity with simulation tools like MATLAB/Simulink and programming languages such as Python or C++ is commonly expected. Strong problem-solving abilities, curiosity, and effective communication help interns collaborate and learn quickly in technical environments. These skills and qualities enable efficient analysis, design, and implementation of control solutions, contributing to successful project outcomes.

What types of projects can an internship control theory engineer expect to work on, and how is mentorship typically provided?

As an Internship Control Theory Engineer, you can expect to work on projects involving modeling, simulation, and analysis of dynamic systems—often supporting the development or improvement of control algorithms for mechanical, electrical, or robotic systems. Interns frequently assist with data analysis, running simulations in tools like MATLAB/Simulink, and performing hardware-in-the-loop testing. Mentorship is commonly provided through regular check-ins with a senior engineer or supervisor, collaborative team meetings, and hands-on guidance during project tasks. This supportive environment helps interns quickly build technical skills and gain exposure to real-world engineering workflows.

What is the difference between Internship Control Theory Engineer vs Control Systems Engineer?

AspectInternship Control Theory EngineerControl Systems Engineer
CredentialsTypically pursuing or recent graduate in control engineering, electrical engineering, or related fieldsBachelor's or master's degree in control engineering, electrical engineering, or related fields
Work EnvironmentInternship setting, often in research labs or development teamsFull-time professional role in industry, manufacturing, or technology companies
Industry UsageUsed for training, skill development, and project support during studiesDesign, implementation, and maintenance of control systems in real-world applications

In summary, an Internship Control Theory Engineer is a temporary, learning-focused role for students or recent graduates, while a Control Systems Engineer is a full-time professional responsible for designing and managing control systems in industry.

What are popular job titles related to Internship Control Theory Engineer jobs in Virginia?

For Internship Control Theory Engineer jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Internship Control Theory Engineer jobs in Virginia look for?

The top searched job categories for Internship Control Theory Engineer jobs in Virginia are:

What cities in Virginia are hiring for Internship Control Theory Engineer jobs?

Cities in Virginia with the most Internship Control Theory Engineer job openings:

Internship Control Theory Engineer jobs near you
Infographic showing various Internship Control Theory Engineer job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, and 4% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.

Embedded Systems & Robotics Engineer

MAG Aerospace

On-site

$80 - $120/hr

Other

Posted 5 days ago

Job description

Position Summary

MAG is staffing for an Embedded Systems & Robotics Engineer who will bridge the critical hardware-software boundary for autonomous tactical systems. You'll modify and enhance systems and solutions that operate independently in GPS-denied environments, from underwater vehicles to aerial swarms, while ensuring reliability in the harshest conditions.

US Citizens Only

Former US Defense Contractor / US Gov / US Military Experience Only

This is a Hybrid Position - Remote mainly - but as well on call to come into a MAG office when requested.

We are seeking candidates who live in proximity to our corporate HQ in Fairfax, VA primarily but will entertain persons living near our satellite offices in:

Aberdeen, MD - Titusville, FL - Newport News, VA - Carthage NC

Essential Duties and Responsibilities

Primary Responsibilities

  • Enhance or augment embedded software for autonomous vehicles (UGV, UAV, UUV, USV) to extend baseline capabilities
  • Implement sensor fusion for autonomous navigation (LIDAR, cameras, IMU, sonar)
  • Design control systems for robotic platforms and actuators
  • Create hardware abstraction layers following MOSA/SOSA standards
  • Develop digital twin simulations for hardware-in-the-loop testing
  • Implement real-time operating systems (RTOS) and safety-critical software
  • Develop and verify safety-critical software in accordance with established standards and best practices
  • Design and fabricate custom hardware solutions using 3D printing and rapid prototyping
  • Apply Model-Based Systems Engineering (MBSE) practices using SysML/AADL
Secondary Responsibilities
  • Lead field testing and validation of autonomous systems
  • Support deployment and troubleshooting in operational environments
  • Create hardware test fixtures and validation procedures
  • Document MOSA compliance and interface specifications
  • Train operators on system capabilities and limitations
Requirements

Experience:

Required Qualifications

  • 5+ years embedded systems and/or robotics development experience
  • Strong proficiency in C and C++ for real-time for resource-constrained systems
  • Expert proficiency and practical knowledge of Python for scripting, tooling, and rapid prototyping
  • Experience with ROS/ROS2 for robotics development
  • Hands-on experience with autonomous vehicle platforms
  • Proficiency with CAD tools and 3D printing/fabrication
  • Understanding of control theory and path planning algorithms
  • Experience with hardware communication protocols (CAN, I2C, SPI, UART)
  • Familiarity with MOSA/SOSA standards and open architectures
  • Experience with simulation tools (Gazebo, MATLAB/Simulink)

Preferred Qualifications

  • Experience with NVIDIA Jetson platforms for autonomous systems
  • Military/defense robotics experience (ROS-M, JAUS)
  • Hands-on experience with RTOS (e.g., FreeRTOS, VxWorks) and/or embedded Linux (Yocto, Buildroot)
  • Knowledge of digital twin technologies and real-time simulation
  • Familiarity with DO-178C, DO-254, or similar safety standards
  • Experience with swarm robotics and distributed controlUnderstanding of SLAM and computer vision for navigation
  • Experience with environmental testing (MIL-STD-810)
  • Pilot's license or experience with FAA Part 107 operations

Education:

  • Bachelor's degree in EE, CE, ME, CS or related field

Clearance:

  • Must be eligible for Secret security clearance
  • US Citizenship required
Special Note What Makes You Successful Here
  • You can go from CAD design to functioning prototype in days
  • You understand autonomy from sensors to behavior planning
  • You apply systems engineering rigor to rapid prototyping
  • You're comfortable with both lab development and field operations
  • You see MOSA as an enabler, not a constraint
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