Defense analytics platform for RF sensor data and missile warning systems
Grey Matters Defense Solutions builds real-time processing pipelines for RF sensor environments and OPIR (overhead persistent infrared) data streams, serving DoD and intelligence agencies. The stack—Python, Java, C/C++, PyTorch, TensorFlow, Kubernetes, and AWS—reflects a mature ML-infrastructure blend tuned for high-frequency data ingestion and low-latency inference. Hiring velocity is accelerating with a mid-to-senior engineering and data team, while internal pain points center on production incident reduction and software delivery automation, suggesting they're scaling from prototype to operational systems.
Grey Matters Defense Solutions is a Denver-based defense contractor founded in 2016, focused on custom software and big-data analytics for the U.S. intelligence community and Department of Defense. The company specializes in two active technical domains: real-time RF signal processing for complex electromagnetic environments, and OPIR sensor data processing for missile warning, missile defense, and battlespace intelligence. With 51–200 employees and active hiring in engineering and data science roles across the United States, the company operates at the intersection of systems engineering and applied machine learning, delivering solutions to classified and unclassified national-security problems.
Core: Python, Java, C/C++, Kubernetes, Docker, AWS (SQS, SNS, CLI). ML: PyTorch, TensorFlow, Keras, scikit-learn. Infrastructure: Jenkins, GitLab, ArgoCD, Rancher, Harbor, Red Hat Enterprise Linux.
Real-time processing pipelines for RF (radio frequency) sensor data in complex environments, and OPIR sensor data processing for missile warning, missile defense, and battlespace awareness applications.
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Grey Matters Defense Solutions, LLC'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 →
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