AI-native wireless platform for spectrum sensing and Open RAN systems
DeepSig builds deep-learning software for wireless communications, working across spectrum sensing, 5G/Open RAN systems, and defense applications. The tech stack—TensorFlow, PyTorch, NVIDIA Sionna, O-RAN, and 3GPP standards—reflects a company solving signal-processing problems with ML rather than traditional DSP. Active projects span 6G research, Open RAN distributed-unit testing, and CI/CD automation for wireless systems, while pain points cluster around deterministic low-latency performance and transitioning R&D into deployable defense systems.
DeepSig develops AI-powered wireless communications software for licensed spectrum, shared spectrum, and Open RAN environments. The company targets tactical and commercial wireless operators, with growing emphasis on defense-sector applications. Core capabilities include spectrum sensing, radio performance optimization, and network automation using deep learning and signal processing. The organization is engineering-heavy (9 of 11 roles) with senior and director-level hiring focus, reflecting the complexity of wireless protocol implementation and ML systems integration required for their customer base.
DeepSig uses TensorFlow, PyTorch, NVIDIA Sionna, O-RAN, 3GPP standards, CUDA, and GPU acceleration. Development spans Python, C++, Java, and Bash, with containerization (Docker, Kubernetes) and CI/CD pipelines for Open RAN system testing.
Active projects include 6G AI/ML research, Open RAN distributed-unit testing, 5G NR system implementation, real-time low-latency applications, CI/CD pipeline automation for wireless systems, and the OmniPhy-5G software product.
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