Job Title: Radio Frequency (RF) Signal Processing Engineer – Deep Learning for Radar Systems Location: Remote / San Francisco Position Type: Full-Time or Part-Time (Flexible for PhD Candidates) Hourly Rate: $40/hour About the Role: We seek a motivated RF Engineer with expertise in deep learning applications for radar detection, phased arrays, and Active Electronically Steered Arrays (AESAs). This role is ideal for candidates passionate about merging cutting-edge AI/ML techniques with advanced radar technologies to solve complex challenges in defense surveillance systems. Key Responsibilities: Design and optimize radar systems, focusing on phased array and AESA technologies. Develop and implement deep learning models (CNNs, RNNs, etc.) for radar signal processing, target detection, and clutter mitigation. Simulate and evaluate radar systems, targets, and environments using numerical simulation software including MATLAB Radar Toolbox, RadarySimPy, RadGen, and others. Collaborate with cross-functional teams to integrate AI-driven solutions into hardware/software platforms. Conduct research on emerging trends in RF systems, machine learning, and adaptive beamforming. Document design processes, test results, and technical reports. Qualifications: Required: Master’s degree in Electrical Engineering, Physics, or related field. Strong background in RF theory, radar systems, phased arrays, and AESAs. Knowledge of digital signal processing (DSP) and radar cross-section (RCS) analysis. Preferred: Current PhD candidate in a relevant discipline. Proficiency in deep learning frameworks (TensorFlow, PyTorch) and programming (Python, MATLAB, C++). Experience working with radar datasets (e.g., SAR, range-doppler maps) and AI model deployment on edge devices. Familiarity with GPU acceleration (CUDA) and optimization techniques for real-time systems. Track record of publications or projects in radar/AI integration. Compensation & Benefits: Competitive hourly rate of $40, with flexible hours for PhD candidates balancing academic commitments. Remote work opportunities.