Embedded Signal Processing Engineer

webAI

1d•Hybrid

About The Position

webAI is seeking an Embedded Signal Processing Engineer to support its Public Sector initiatives. This role focuses on building and optimizing production-ready AI systems for secure and distributed environments. The position is at the intersection of real-world tactical hardware, machine learning, signals processing, and multisensor engineering, translating them into autonomous field deployment. The engineer will be responsible for deploying and prototyping AI models into embedded hardware systems for government edge environments in restricted and/or disconnected environments.

Requirements

6+ years of professional experience in RF and networking architecture, tactical radio systems, physical bench-test simulation environments, and distributed middleware.
Hands-on experience with embedded systems, signal processing, and custom hardware integration.
Strong understanding of physical SWaP-C optimization, network partitioning, multi-stream ingestion and cross-platform development across systems like x86 and Jetson/ARM64.
Demonstrated expertise in C/C++ and Linux
Bachelor’s degree in a relevant field, or equivalent practical experience/military service. Advanced field experience is heavily preferred.

Nice To Haves

Experience developing, testing, or deploying autonomous software on tactical military or defense systems and open architecture standards.
Proven experience conducting field validation, site calibration, or operational testing of edge networks and ruggedized hardware in civilian commercial or tactical defense environments.

Responsibilities

Coordinate with AI and Network Software Engineers to design low-latency multi-node communication frameworks in restricted and/or disconnected environments.
Quantize, compile, and deploy real-time multi-agent pipelines for readiness across diverse edge architectures.
Develop algorithms for asynchronous multimodal data fusion, tracking, and signal processing.
Architect and maintain high-fidelity Hardware-in-the-Loop simulation environments to test autonomy algorithms.
Lead physical assembly, system calibration, and ruggedized field-testing of multi-node prototypes in unstructured environments.
Up to 25% travel to other webAI office locations, along with government field and test sites across the country