WebAI
Embedded Signal Processing Engineer
About this role
webAI seeks an Embedded Signal Processing Engineer to deploy and optimize AI models on ruggedized edge hardware for government applications in disconnected environments. You'll design low-latency communication frameworks, develop multimodal fusion algorithms, and conduct field validation of autonomous systems across diverse architectures.
What you'll do
- Coordinate with AI and network engineers to design low-latency multi-node communication for restricted/disconnected environments
- Quantize, compile, and deploy real-time multi-agent pipelines across diverse edge architectures
- Develop asynchronous multimodal data fusion, tracking, and signal processing algorithms
- Build and maintain Hardware-in-the-Loop simulation environments for autonomy testing
- Lead physical assembly, calibration, and ruggedized field testing of multi-node prototypes
- Travel up to 25% to office locations and government field test sites
What they're looking for
- RF and networking architecture
- Tactical radio systems and distributed middleware
- Embedded systems and custom hardware integration
- C/C++ and Linux development
- Signal processing and digital signal design
- SWaP-C optimization and network partitioning
- x86 and ARM64/Jetson cross-platform development
- Hardware-in-the-Loop simulation
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WebAI
WebAI builds AI infrastructure and platform solutions that help enterprises deploy and optimize machine learning systems at scale. The company is hiring Design Engineers, Software Engineers, Data Platform Engineers, Forward Deployed Engineers, and AI Software Engineers to develop everything from web experiences and AI prototypes to data connectors and distributed infrastructure.
View all jobs at WebAILikely interview questions
- Describe your experience designing and testing RF communication systems in restricted or disconnected network environments.
- Walk us through a project where you optimized embedded algorithms for SWaP-C constraints across different hardware platforms.