Principal Signal Processing Engineer

What You'll Do

• Develop advanced signal processing algorithms for RF sensing, spectrum awareness, electronic warfare and radar with a particular emphasis on pulsed-radar and time-varying RF phenomenology.
• Build and analyze radar and RF sensing products including range-Doppler maps, spectrograms, channelized data products, pulse descriptor words, pulse-train observables, geolocation outputs, and other mission-relevant data products.
• Prototype and validate algorithms using Python, MATLAB, C/C++, or similar tools, then work with software and systems engineers to transition them into deployed systems.
• Analyze real-world RF data collected in lab, vehicle, and field environments to characterize performance, diagnose issues, and improve sensing capability under operationally realistic conditions.
• Collaborate with RF, embedded software, autonomy, systems, and integration engineers to deploy signal processing capabilities onto autonomous ground vehicle platforms.
• Support field testing, demonstrations, experimentation, and operational validation of EMSO capabilities.
• Work with external vendors, government partners, and internal teams to integrate signal processing capabilities with COTS, GOTS, SDR, radar, EW, and SIGINT systems.

What We're Looking For

• Mission-first engineer who prioritizes operational relevance and customer outcomes.
• Owner who takes responsibility, handles ambiguity well, and drives work from concept through fielded capability.
• Technically deep builder with strong curiosity across DSP, RF sensing, autonomy, and real-world system performance.
• Background in algorithms for pulse compression, matched filtering, coherent and non-coherent integration, Doppler processing, CFAR detection, beamforming, adaptive filtering, interference mitigation, clutter rejection, and signal detection in dense or contested RF environments.

Minimum Qualifications

• 10+ years of experience developing signal processing algorithms for RF, radar, communications, EW, SIGINT, sonar, or related sensing systems.
• Strong understanding of digital signal processing fundamentals, including detection theory, estimation, filtering, spectral analysis, sampling theory, modulation, synchronization, and statistical signal processing.
• Hands-on experience taking algorithms from analysis or simulation into working software systems.
• Experience processing real-world sensor data and validating algorithm performance against measured data, not only idealized simulations.
• Programming experience in Python, MATLAB, C/C++, or similar languages for algorithm development, data analysis, and test automation.
• Experience with radar or RF signal-processing problems involving pulsed emitters, signal identification, tracking, and geolocation.
• Ability to work cross-functionally with RF, software, systems, autonomy, and hardware engineers.
• Bachelor’s degree in Electrical Engineering, Computer Engineering, Applied Physics, Mathematics, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience with radar signal processing, including range-Doppler processing, pulse compression, matched filtering, coherent integration, non-coherent integration, CFAR detection, clutter mitigation, waveform analysis, MIMO radar, SAR, ISAR, GMTI, or track-before-detect methods.
• Experience with RF signal processing for EMSO, EW, SIGINT, ELINT, COMINT, spectrum monitoring, direction finding, geolocation, or electronic support systems.
• Experience with antenna arrays, beamforming, adaptive arrays, angle-of-arrival estimation, interferometry, phased-array processing, or multi-sensor geolocation techniques such as TDOA/FDOA/AOA fusion.
• Experience with software-defined radios, high-rate digitizers, RFSoC platforms, radar front ends, or other RF sensing hardware.
• Experience implementing or optimizing real-time signal processing systems; GPU implementation experience using CUDA, cuSignal, CuPy, OpenCL, or similar platforms is a strong plus.
• Experience with embedded, edge, or low-latency deployment constraints, including throughput, memory bandwidth, timing, and data-movement tradeoffs.
• Experience working with field-collected RF data in noisy, cluttered, contested, or operationally realistic environments.
• Advanced degree, M.S. or Ph.D., in Electrical Engineering, Applied Physics, Mathematics, or a related field.
• Prior experience working in fast-paced, small-team, or field-focused development environments.