RF & Signal Processing Engineer

We are seeking an experienced RF & Signal Processing Engineer to lead development and optimization efforts in Direction Finding (DF) accuracy and system performance for advanced EW systems.

Key responsibilities:

• Design and develop advanced DF algorithms such as Phase Interferometry, Amplitude Comparison, Time Difference of Arrival (TDOA), Angle of Arrival (AOA), Triangulation and Correlation-based methods
• Implement algorithmic techniques to improve bearing estimation accuracy, resolution, and update rate.
• Perform signal detection, correlation, noise suppression, SNR enhancement, and multi-channel calibration.
• Design adaptive filtering and signal conditioning algorithms to ensure reliable DF performance under dynamic conditions.
• Evaluate algorithmic performance using lab-captured, and field-collected data.
• Identify and mitigate performance bottlenecks such as phase noise, antenna mismatch, or hardware impairments.
• Work with system integration teams to align DF algorithms with hardware constraints and operational scenarios.
• Prototype and validate DSP algorithms in Python (NumPy, SciPy, Matplotlib) and MATLAB for signal acquisition, filtering, and spectral analysis.
• Translate high-level algorithms into efficient real-time code for embedded deployment using C/C++ or optimized libraries.
• Implement parallelization, multi-threading, or vectorization (SIMD) techniques to achieve real-time performance.
• Optimize algorithms considering latency, throughput, power consumption, and memory footprint constraints.
• Collaborate with firmware and hardware teams to deploy algorithms on DSPs, FPGAs, or SDR platforms.
• Work with RF design teams to understand and model front-end characteristics such as LNA gain, filter responses, phase imbalance, and antenna coupling.
• Support calibration procedures to correct RF non-idealities affecting DF performance.
• Conduct link budget analysis, path loss modeling, and RF propagation studies for system-level optimization.
• Participate in field testing, data collection, and environmental tuning to validate algorithm performance in real-world EW conditions.
• Optimize DSP algorithms for real-time wireless communication under resource and performance constraints.