Principal Signal Processing Engineer

About Forterra

Forterra is a leading provider of autonomous systems for ground-based movement in the working world. Amongst some of the earliest innovators in the field of driverless technology, Forterra is focused on building systems that protect front‑line soldiers and enable civilian workers in our industrial base. Forterra is the go‑to provider of ground autonomy solutions for the U.S. Department of Defense, which harnesses the technology for asymmetric warfare in critical conditions.

As an extension of our core products in Command, Control, and Communications (C3), Forterra is expanding deeper into the Electromagnetic Spectrum Operations (EMSO) space to improve the survivability of the systems and platforms we integrate. We are building capabilities that provide broad spectrum awareness, enable rapid identification of signals of interest, and support open, plug‑and‑play integration with government and partner systems.

We are seeking a highly experienced signal processing engineer to design, prototype, and field advanced RF and radar signal processing capabilities for Forterra’s EMSO products. This role is centered on turning complex signal environments into actionable sensing, awareness, and decision‑quality outputs for autonomous platforms operating in real‑world conditions.

You will own signal processing development end‑to‑end, from algorithm design and analysis through implementation, integration, field test, and performance validation. This is a hands‑on role for an engineer who can move fluidly between theory, simulation, software implementation, hardware constraints, and over‑the‑air system performance.

• Develop advanced signal processing algorithms for RF sensing, spectrum awareness, electronic warfare and radar with a particular emphasis on pulsed‑radar and time‑varying RF phenomenology.
  * Build and analyze radar and RF sensing products including range‑Doppler maps, spectrograms, channelized data products, pulse descriptor words, pulse‑train observables, geolocation outputs, and other mission‑relevant data products.
• Prototype and validate algorithms using Python, MATLAB, C/C++, or similar tools, then work with software and systems engineers to transition them into deployed systems.
• Analyze real‑world RF data collected in lab, vehicle, and field environments to characterize performance, diagnose issues, and improve sensing capability under operationally realistic conditions.
• Collaborate with RF, embedded software, autonomy, systems, and integration engineers to deploy signal processing capabilities onto autonomous ground vehicle platforms.
• Support field testing, demonstrations, experimentation, and operational validation of EMSO capabilities.
  * Work with external vendors, government partners, and internal teams to integrate signal processing capabilities with COTS, GOTS, SDR, radar, EW, and SIGINT systems.

• Mission‑First Mindset - We put the needs of the mission and
  * A mission‑first engineer who prioritizes operational relevance and customer outcomes.
• An owner who takes responsibility, handles ambiguity well, and drives work from concept through fielded capability.
• A technically deep builder with strong curiosity across DSP, RF sensing, autonomy, and real‑world system performance.
• Someone who has a background in algorithms for pulse compression, matched filtering, coherent and non‑coherent integration, Doppler processing, CFAR detection, beamforming, adaptive filtering, interference mitigation, clutter rejection, and signal detection in dense or contested RF environments.

• 10+ years of experience developing signal processing algorithms for RF, radar, communications, EW, SIGINT, sonar, or related sensing systems.
• Strong understanding of digital signal processing fundamentals, including detection theory, estimation, filtering, spectral analysis, sampling theory, modulation, synchronization, and statistical signal processing.
• Hands‑on experience taking algorithms from analysis or simulation into working software systems.
• Experience processing real‑world sensor data and validating algorithm performance against measured data,…