About the Role
- Shield AI's Software Development Engineer Intern program spans engineers who design, build, and test the code that powers our autonomous systems — from user-facing applications and embedded flight software to machine learning models and the underlying systems platforms that tie it all together. Over 10–12 weeks, interns work alongside full-time engineers to analyze requirements, write and debug production-quality code, and ship a real feature or capability using our standard Agile development practices.
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Applications: Build a new feature or internal tool (web, mobile, or desktop) that streamlines a mission-planning or fleet-management workflow.
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Firmware/Embedded: Develop and debug embedded C/C++ code for a flight controller or sensor module, including bring-up and hardware-in-the-loop testing.
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Machine Learning: Train, evaluate, and integrate a perception or decision-making model (e.g., object detection, sensor fusion) into an autonomy pipeline.
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Systems Development: Extend a platform tool, API, or data pipeline that supports autonomy software, simulation, or cloud infrastructure.
Example Intern Projects
Required Qualifications
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Currently pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field
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Proficiency in at least one modern programming language (e.g., C, C++, Python, Java, or JavaScript)
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Solid foundation in data structures, algorithms, and software design principles
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Experience writing, testing, and debugging code, whether through coursework, personal projects, or prior internships
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Familiarity with version control (e.g., Git) and collaborative development workflows
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Strong analytical and problem-solving skills, with the ability to break down ambiguous requirements into working code
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Effective written and verbal communication skills and the ability to work collaboratively in a team environment
Preferred Qualifications
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Exposure to mobile or web application frameworks and full-stack development
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Hands-on experience with embedded systems, microcontrollers, real-time operating systems, or assembly-level debugging
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Coursework or projects involving machine learning, statistics, probability theory, or deep learning frameworks (e.g., PyTorch, TensorFlow)
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Experience with cloud platforms, databases, networking, or distributed systems
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Familiarity with Agile/Scrum development methodologies
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Prior internship, research, or club/competition experience in robotics, autonomy, or aerospace applications
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Interest in or exposure to the defense, aerospace, or autonomous systems industry