Develop and integrate DSP and AI/ML algorithms onto embedded hardware for advanced AI/ML technologies.
Requirements
Experience with developing and integrating DSP and AI/ML algorithms into embedded systems
Experience in real-time operating systems development including task and thread management targeting command and control of FPGA resources
Experience in task and thread management for command and control of FPGA resources, with expertise in Xilinx FPGA architectures (e.g., Zynq UltraScale+, Kintex, Artix) and AMD embedded devices, including AMD Versal, Xilinx RFSoC, and Xilinx MPSoC
Experience with AMD embedded devices including AMD Versal, Xilinx RFSoC, and Xilinx MPSoC
Strong programming skills in languages such as C and C++, and Python
FreeRTOS and/or bare metal application development
Xilinx development tools such as Vivado Design Suite, Vitis and PetaLinux
Responsibilities
Integrate, test, and validate DSP and AI/ML algorithms on embedded devices
Deploy algorithms for integration and field testing events on real-time, SWaP hardware
Develop and architect best practices for algorithm integration
Algorithm integration into embedded devices, including researching advanced accelerators for future embedded systems
Algorithm integration into embedded devices
Other
Master’s or PhD degree in embedded programming with FPGA-specific experience or a closely related field
Must be willing to travel as projects requires; estimated average travel is once every quarter for between 2 days up to 1 week (~10%)
Must be a U.S. Citizen
Must hold or be eligible to obtain and maintain a U.S. security clearance
