Sydney, NSW / Full-Time DroneShield is seeking a FPGA DSP Engineer with relevant experience to join the team in Sydney, Australia. The position will report to VP, Embedded Systems. The core challenge of the role is the development and expansion of our drone recognition and disruption algorithms using software-defined radios (SDRs). Implementing complex Digital Signal Processing algorithms into production grade firmware. Responsibilities, Duties and Expectations The work is predominantly technical and requires an understanding of radio frequency (RF) concepts, FPGA and ARM processor development, digital signal processing, related hardware technology, test equipment and/or communication systems Research, scoping, design, development, and implementation of embedded software systems to support real-time wide frequency spectrum RF digital data signal processing Proprietary and open standard transmission protocol identification and data recovery Optimise the core of DroneShield's technology for recognition, accuracy, performance, stability, and maintenance Qualifications, Experience and Skills BS degree in Electronic Engineering, similar technical field of study or equivalent practical experience 3 years of qualified experience working within an established team Strong experience with programming, debugging, and verifying Verilog, VHDL or SystemVerilog Strong FPGA development experience using FPGA software tools such as Vivado (preferable), Quartus, Vitis, etc Experience with designing and implementing high-throughput, low-latency and fully pipelined FPGA architectures Experience using and designing automated Verification and Validation frameworks Experience writing C/C++ firmware for FPGA modules along with familiarity with scripting languages (Python Preferable) Experience working in a Linux environment Experience working with PCB schematics, board bring-ups and debugging hardware is highly desirable A general RF background and knowledge of RF transmission protocols and general principals is desirable Strong background and experience in Digital Signal Processing is highly desirable Understanding or working knowledge of Machine Learning (ML) concepts within the scope of FPGA implementation would be ideal