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webAI is building distributed AI infrastructure for edge deployment, enabling enterprises to run large-scale AI models on consumer hardware while keeping data private. The company focuses on secure, scalable AI systems for real-world deployment in restricted and disconnected environments.
As an Embedded Signal Processing Engineer, you will support public sector initiatives by deploying and prototyping AI models into embedded hardware systems for government edge environments. This role bridges tactical hardware, machine learning, signal processing, and multisensor engineering.
Key responsibilities include:
- Coordinate with AI and Network Software Engineers to design low-latency multi-node communication frameworks for restricted/disconnected environments
- Quantize, compile, and deploy real-time multi-agent pipelines 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 for autonomy algorithm testing
- Lead physical assembly, system calibration, and ruggedized field-testing of multi-node prototypes in unstructured environments
- Travel up to 25% to webAI offices and government field/test sites across the country
Required qualifications:
- 6+ years of professional experience in RF and networking architecture, tactical radio systems, physical bench-test simulation, and distributed middleware
- Hands-on embedded systems, signal processing, and custom hardware integration experience
- Strong understanding of SWaP-C optimization, network partitioning, multi-stream ingestion, and cross-platform development (x86, Jetson/ARM64)
- Demonstrated C/C++ and Linux expertise
- Bachelor's degree in relevant field or equivalent practical/military experience
Preferred: Experience with autonomous software on tactical military/defense systems, field validation, site calibration, or operational testing of edge networks and ruggedized hardware.
The company will provide training in AI/ML aspects including computer vision and edge AI systems. webAI values truth, ownership, tenacity, and humility.
