Linux embedded (Python + C/C++)

Job Title: Linux embedded (Python + C/C++)Location: Irving, TX(Onsite)RolePort and optimize a containerized video analytics pipeline to run on CPU-constrained router hardware (Cradlepoint OS, Wi-Fi 7 PrplOS, FWA routers). You'll own the full stack: model optimization, container architecture, and on-device inference performance.---What You'll Do- Port GPU-based video analytics models (object detection, classification) to CPU-only router targets- Optimize inference pipeline to stay under 100MB memory footprint using SLMs- Build containerized architecture with dynamic cloud-driven model loading- Tune accuracy/performance tradeoffs on ARM/MIPS router hardware- Integrate with Cradlepoint OS and PrplOS environments- Benchmark and iterate on detection accuracy vs. latency on constrained hardware---Required- 4+ years in embedded systems or edge ML deployment- Experience with containerization (Docker, LXC) on constrained devices- ML model optimization: quantization, pruning, ONNX, TensorFlow Lite, OpenVINO- Video analytics / computer vision (YOLO variants, object detection pipelines)- Python + C/C++ on Linux embedded targets- Cross-compilation, profiling, and memory optimization---Strong Plus- Cradlepoint NetCloud / PrplOS / OpenWRT experience- NPU/DSP acceleration on router-class SoCs- DeepStream or similar inference pipeline experience (GPU→CPU migration)- SLM deployment (sub-1B parameter models on edge)- RTSP/video streaming on embedded Linux---You Are- Comfortable with no GPU — CPU-only inference is the constraint, not a fallback- Pragmatic about accuracy tradeoffs at the edge- Experienced navigating vendor OS lock-in and limited debugging toolchains