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Salary: USD 173,000 - 196,000 / annual
Muon Space, a LEO satellite constellation provider founded in 2021, seeks an FPGA RF Signal Processing Engineer to join its High Performance Compute team in San Jose. This hybrid role (3 days/week on-site) focuses on implementing and optimizing RF processing algorithms on FPGAs for real-time execution in Earth observation and remote sensing applications.
You will design, simulate, and integrate digital signal processing (DSP) and modulation algorithms for RF applications including communications, electronic signal monitoring (ESM), and radar. Core responsibilities include translating prototype algorithms into FPGA implementations using RTL/HDL (Verilog, SystemVerilog, VHDL), collaborating with RF hardware engineers on system bring-up and calibration, and authoring technical documentation and test reports.
Required qualifications include a BS/MS in Electrical Engineering or related field, 3+ years of professional FPGA development experience with RF algorithms, and deep expertise in RF digital signal processing techniques (spectrum monitoring, modulation/demodulation, filtering, channel estimation, synchronization, AGC, DPD). You must have profound knowledge of RTL/HDL and FPGA system architecture, ability to work with distributed interdisciplinary teams, and familiarity with modern software development practices. U.S. security clearance eligibility is required; active clearance is a plus.
Preferred qualifications include experience with Xilinx/AMD RFSoC or MPSoC, proficiency in C/C++ or Rust for embedded systems, Python-based development, FPGA-based DSP techniques (beamforming, MIMO, radar processing, communications modulation schemes), space-based applications, CI/CD pipelines, Git version control, JTAG debugging, and lab instrumentation.
The role demands a systems-level mindset connecting RF physics, DSP mathematics, and FPGA implementation, strong analytical and debugging skills for RF/FPGA hardware issues, and excellent communication abilities. You'll work at the intersection of RF theory, algorithm development, software-defined radio (SDR), and high-performance digital design to deliver next-generation wireless communication and RF sensing products.