What you will do Design and build the RF sensing subsystem for our distributed detection nodes, from antenna selection through SDR integration to real-time signal processing software
Develop detection and classification for drone control and video links, including common commercial protocols, Wi-Fi based links, and custom or nonstandard emitters
Build robust performance in dense RF environments: urban clutter, industrial sites, and event settings where thousands of benign emitters compete with the signal you care about
Optimize for edge deployment: real-time processing on embedded compute, low power budgets, and operation without cloud connectivity
Work with our vendor partners on SDR hardware selection and integration
Take your subsystem into the field: bench testing, outdoor range testing, cold-weather characterization, and installation on customer sites
Collaborate closely with the founding team on sensor fusion, helping define how RF tracks combine with acoustic and visual detections
Help shape the engineering culture, tooling, and hiring of a team that will grow around you
What we are looking for 5+ years of hands-on RF or wireless systems engineering, or equivalent depth from research, defense, or responsible personal work
Strong software-defined radio experience: GNU Radio, custom DSP pipelines,



or equivalent frameworks on platforms such as USRP, Per Vices, or similar
Solid digital signal processing fundamentals: detection theory, filtering, spectral analysis, and working in low SNR conditions
Proficiency in C++ and Python for real-time signal processing
Experience with at least one of: drone RF protocols, wireless protocol reverse engineering, spectrum monitoring, electronic warfare, or radar
Comfort with hardware: you can work with antennas, front ends, and test equipment, and you are willing to stand in a field in February to prove your system works
Eligibility to work in Canada and ability to obtain Canadian security clearance and Controlled Goods Program registration
Nice to have Experience with embedded Linux and edge compute platforms (NVIDIA Jetson or similar)
Direction finding, TDOA, or multi-sensor geolocation experience
Background in counter-UAS, EW, SIGINT, or spectrum sensing
Familiarity with FPV drone ecosystems and their radio links (ExpressLRS, analog video, digital video links)
Machine learning applied to RF signal classification
Prior experience at an early-stage startup or on a small team shipping hardware

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📌 RF Engineer (Ontario)
🏢 Dawn Recruiting Agency
📍 Ontario