Drimva

STR

Principal Signal Processing Engineer

$206K–$284K

Woburn, MA +1 · Principal · Full-time · Posted Oct 14, 2026

Location
Woburn, MA
Woburn, Massachusetts, United States
Experience
8+ years on EW or Radar programs; 2+ years in two or more specified technical areas.
Education
PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or a related technical discipline.

About the job

Develops and applies algorithms for radar and RF sensing and counter-sensing, leads research teams, and helps demonstrate prototype system capabilities.

What you'll do

  • Engage with customers to understand requirements and shape technical solutions.
  • Develop signal processing and machine learning techniques for radar and RF challenges; collaborate on prototype systems.
  • Lead multidisciplinary teams and support business development and proposal writing.

What they ask for

  • Ability to obtain a Top Secret security clearance; U.S. citizenship is needed by the U.S. Government.
  • PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or a related technical discipline.
  • 8+ years of experience on EW or Radar programs, including developing sensor system modes and advanced signal- and data-processing algorithms through testing and verification.
  • 2+ years of experience in two or more listed areas, such as RF/radar signal processing, optimization, waveform design, electronic warfare, machine learning, or algorithm development.

Nice to have

  • Active Secret or TS/SCI Clearance; demonstrated leadership of complex research, development, and engineering efforts.
  • Advanced degree or experience with defense-sector radar/RF technologies, machine learning methods, or translating mission needs into end-to-end solutions.

Pay

$206,000 - $284,000 USD base salary

Tools

MATLAB, Python, C/C++, PyTorch, Ray, TensorFlow/board, MLflow

AI focus

Applies machine learning to radar and RF sensing and counter-sensing; preferred experience includes NLP, image recognition, semantic segmentation, reinforcement learning, Bayesian methods, deep convolutional and graph neural networks.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)