Integer Technologies is looking to develop and secure cyber-physical systems, with a focus on integrating Agentic AI, Large Language Models (LLMs), and Small Language Models (SLMs) into autonomous maritime craft for the Department of Defense and other U.S. Government agencies.
Requirements
- Basic experience with computer applications or software languages. Experience with Python programming is highly desired, as well as familiarity with GitHub.
- An understanding of cybersecurity principles, to include threat modeling, vulnerability assessments, and mitigation strategies.
- Strong interest in Agentic AI and Machine Learning.
- Experience in using Python for AI/ML development, with an understanding of Agentic AI, LLMs, and SLMs.
- Familiarity with AI/ML frameworks such as PyTorch, TensorFlow, or similar tools.
- Interest in unmanned vehicles, including Unmanned Undersea Vehicles (UUVs), Unmanned Surface Vehicles (USVs), and Unmanned Aerial Vehicles (UAVs).
- Those with cybersecurity-related certifications (OSCP, Security+, CEH, etc) or presently working on certifications encouraged to apply.
Responsibilities
- Learn and apply fundamental principles of AI and cybersecurity, focusing on securing autonomous submersible and surface maritime systems with AI-driven cybersecurity solutions, including Agentic AI, LLMs, and SLMs.
- Assist with developing and implementing cybersecurity frameworks to protect uncrewed surface vessels and uncrewed underwater vessels.
- Gain experience in threat modeling, vulnerability assessments, and red team exercises to identify and mitigate risks in cyber-physical systems.
- Assist with building, validating, and securing AI/ML frameworks using Python.
- Contribute to the development of decision support frameworks for cybersecurity in uncrewed systems.
- Assist with documenting research findings and technical solutions.
Other
- Must be a U.S. Citizen.
- A senior in a bachelor's degree program or a post-graduate student in a relevant field (e.g., computer science, cybersecurity, electrical engineering, or related).
- Capable of working unsupervised after training.
