Lead GPU Software Engineer

About the Team: The Sensors Division at STR focuses on technology development for advanced sensor systems, particularly in the areas of airborne/surface-based radar, electronic warfare, underwater acoustics, hyperspectral imaging, and EO/IR sensing. Within this role, we perform work on full system prototypes, experiment campaigns and technology component development. Development roles within the Sensors Division include RF analog/digital hardware, acoustic hardware, signal processing algorithms, machine learning algorithms, tracking/fusion, as well as real-time embedded processor implementation. Within the Sensors Division, the Real-time Architectures, Integration and Demonstration (RAID) Group focuses on transition of algorithms from concept to real-time software, providing open architecture expertise, and facilitating integration of capabilities for experimentation, test, and deployment. The Role: The RAID Group is seeking a Lead Software Engineer with demonstrated expertise in GPU programming and optimization to design, develop, and implement real-time software for RF sensor systems compliant with open architecture standards. You will work as part of focused teams to transition advanced signal processing algorithms from research prototypes into production-quality software for embedded and distributed computing platforms. You will be responsible for architecting software components, implementing real-time processing pipelines, and optimizing performance for resource-constrained systems. A successful candidate will have experience developing high-performance C/C++ software for sensor systems. Strong understanding of real-time systems, multithreaded programming, and signal processing are essential. Experience with open architecture frameworks and standards is highly desired. Strong technical, interpersonal, and communication skills are important for working in collaborative, multi-disciplinary teams. What you will do: Design and implement real-time software components for RF sensor signal processing systems Develop and optimize GPU-accelerated algorithms for signal processing pipelines using CUDA Translate algorithm specifications (MATLAB, Python) into optimized C/C++ implementations Architect software components compliant with open architecture standards Integrate and optimize code for real-time performance on multi-core CPUs and GPUs with strict latency requirements Develop unit tests, integration tests, and performance benchmarks; promote testing best practices Document software designs, APIs, implementation details, and technical reports Contribute to briefings and presentations for program reviews and customer meetings Collaborate with algorithm developers, systems engineers, RF hardware engineers, and integration teams across programs Contribute to proposal development efforts including technical approach Perform peer reviews and suggest next steps for technical work Support approximately 20% travel…