Why This Role Stands Out
This hybrid role offers a fantastic opportunity to develop cutting-edge signal processing software for critical national security systems, leveraging GPU acceleration and AI-assisted tools for significant career growth. You'll thrive here if you're a mid-senior engineer passionate about RF sensing, algorithm development, and collaborative problem-solving within a reputable organization. Apply now to contribute to advanced radar technology and expand your expertise in a dynamic and impactful environment.
Quick Overview
Job Description
Software Signal Processing Engineer Program Description: Our client is prime on a program that will field a resilient ground-based radar system providing our nation with significantly enhanced space domain awareness for geostationary orbit. They are looking to bring on a Software signal processing engineer immediately. Day to Day Responsibilities: Design, develop, test, and optimize software applications supporting advanced digital signal processing (DSP) capabilities for RF sensing and tracking systems.
Develop, implement, and refine signal processing algorithms for detection, estimation, calibration, filtering, FFT analysis, peak detection, and target characterization. Apply theoretical signal processing principles to solve complex engineering challenges involving RF data, sensor calibration, range/range-rate estimation, orbital tracking, sensor coupling, and signals of opportunity. Collaborate with software, systems, RF, hardware, and algorithm engineers to integrate signal processing solutions into operational software systems.
Develop high-performance software using GPU acceleration techniques (CUDA, NVIDIA MatX, parallel computing) for computationally intensive signal processing workloads. Analyze system performance, validate algorithm effectiveness, troubleshoot signal anomalies, and optimize processing pipelines. Support software development throughout the full engineering lifecycle including design, implementation, testing, verification, documentation, and deployment.
Leverage AI-assisted engineering tools to improve software development efficiency while maintaining full engineering ownership and technical review of generated code.
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