Drimva

CoVar

Signal Processing Engineer

Durham, NC +1 · Full-time · Posted Sep 8, 2025

Location
Durham, NC
Durham, North Carolina, United States
Experience
3+ years in RF signal processing or a related discipline.
Education
B.S., M.S., or Ph.D in Electrical Engineering, Computer Engineering, Applied Physics, Applied Mathematics, or a related field.

About the job

Develops and evaluates RF signal-processing algorithms and software for customer applications, including detection, localization, classification, tracking, and electronic warfare.

What you'll do

  • Design, implement, and optimize signal- and array-processing algorithms for RF applications.
  • Analyze RF datasets and develop simulations and prototypes; evaluate performance using real-world data and laboratory or field testing.
  • Integrate DSP algorithms into RF systems and prepare technical reports and presentations.

What they ask for

  • B.S., M.S., or Ph.D. in Electrical Engineering, Computer Engineering, Applied Physics, Applied Mathematics, or a related field.
  • 3+ years of experience in RF signal processing or a related discipline.
  • Proficiency in one or more of Python, C/C++, or MATLAB, and experience in at least one listed area such as RF signal processing, electronic warfare, optimization, array processing, or AI/ML algorithm development.
  • Ability to work in Durham, NC, and eligibility for US security clearance.

Nice to have

  • Experience with DoD radar signal processing and electronic warfare applications; spectrum monitoring and machine-learning signal classification.
  • Familiarity with FPGA or GPU acceleration, C/C++ for embedded or real-time applications, or an active U.S. security clearance.

Tools

Python, MATLAB, C/C++, FPGAs, GPUs, SDRs

AI focus

Develops AI/ML algorithms for RF applications; preferred areas include computer vision, reinforcement learning, natural language processing, and machine-learning-based spectrum monitoring and signal classification.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 4, 2026 (UTC)