Radar/Sonar Systems Engineer
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The job description
Tech stack. MATLAB, Python (NumPy, SciPy), digital signal processing, digital beamforming, CFAR detection, Kalman and particle tracking filters, pulse compression, STAP, CUDA
About the role
You will join a defense technology company building radar and sonar systems that find faint targets in heavy clutter, across air, surface, and undersea domains. The sensing team turns raw multi-channel array data into tracks a commander can trust, spanning waveform design, beamforming, adaptive processing, and multi-target tracking. Your algorithms decide what counts as a detection, how beams are formed and steered, and how tracks survive maneuvers, missed detections, and deliberate interference.
What you will achieve
- Design detection processing chains, including pulse compression and CFAR detectors, that hold false alarm rates below specification while lifting detection range by 10 percent or more.
- Implement digital beamforming for a multi-channel array, demonstrating sidelobe control and null steering against simulated jammers in the lab.
- Build multi-target tracking filters using Kalman and particle methods that maintain track continuity through maneuvers and missed detections.
- Prototype space-time adaptive processing that suppresses ground or sea clutter by 20 dB or better in recorded data trials.
- Deliver algorithm performance reports with ROC curves, Monte Carlo statistics, and clear margins against the system requirement set.
What you will bring
Must-haves
- You bring 2 to 5 years of experience in radar, sonar, or array signal processing algorithm development.
- You are strong in detection and estimation theory, including matched filtering, CFAR, and ambiguity analysis.
- You have implemented beamforming, direction finding, or adaptive processing on real or simulated array data.
- You code fluently in MATLAB and Python for algorithm prototyping, simulation, and data analysis.
- You understand tracking fundamentals such as data association, gating, and state estimation with Kalman variants.
- You can explain algorithm tradeoffs between detection performance, computational load, and latency to system architects.
- You have validated algorithms against recorded sensor data, quantifying detection and tracking performance with statistically sound methods.
Nice-to-haves
- You have accelerated signal processing code with CUDA or on FPGA targets.
- You bring experience with sonar propagation modeling or underwater acoustics.
- You have worked with recorded radar or sonar data from field collections or trials.
- You are eligible for a U.S. security clearance.
- You bring experience with real-time implementation constraints, including fixed-point effects and processing latency budgets.
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