AI/ML and autonomy systems for defense and national security
MORSE builds AI/ML decision systems, mission planning platforms, and autonomous vehicle software for U.S. defense and national security customers. The tech stack spans Python, C++, Rust, MATLAB, Kubernetes, and specialized autonomy libraries (ROS, PX4, Ardupilot), with active adoption of lower-level C/C++ — a shift suggesting migration of algorithms from prototyping environments into constrained embedded and real-time systems. Leadership and senior-level hiring dominates (24 of 36 open roles), indicating scaling of technical depth rather than pure headcount.
Notable leadership hires: Chief Engineer
MORSE, founded in 2014 and headquartered in Cambridge, MA, is an employee-owned firm of scientists, engineers, and software developers serving the U.S. national security ecosystem. The company specializes in algorithm development, software engineering, and system integration across machine learning, artificial intelligence, computer vision, mission planning, guidance and navigation, and unmanned aerial vehicle autonomy. Current projects center on AI/ML model evaluation, real-time embedded algorithm deployment, command-and-control systems, and battle management applications. The organization operates at 201–500 employees and is actively hiring across engineering and data roles in the United States and United Kingdom.
MORSE uses AWS, Azure, GCP, Python, C++, Kubernetes, Docker, React, MATLAB, ROS, PX4, Ardupilot, LIDAR, SolidWorks, and Terraform. The company is actively adopting C/C++ and has been transitioning away from Python.
MORSE focuses on AI/ML model testing and evaluation, mission planning platforms, command-and-control systems, autonomous vehicle guidance and navigation, and transitioning algorithms from research into real-time embedded systems for defense applications.
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MORSE Corp's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.