Embedded Ai Engineer

AI Summary

Job Description

Develop and optimize embedded AI inference pipelines for real-time object detection, tracking, and classification on edge devices. Deploy vision models (YOLO, CNN, RNN, OCR) on AI accelerators like Hailo and Jetson, performing quantization, pruning, and hardware-aware optimization while collaborating with AI researchers and contributing to edge system architecture.

Hard Requirements

• Proficient in C/C++ and Python for embedded development and AI integration
• Experience with quantization, pruning, and model conversion (ONNX, TFLite, TensorRT)
• Hands-on experience with at least one AI hardware platform (Hailo, Jetson, Movidius, ARM Ethos-U, Coral)
• Solid understanding of deep learning architectures (CNN, YOLOv5/v8, OCR, ReID, RNNs)
• Strong knowledge of video/image processing pipelines (GStreamer, OpenCV)
• Experience with Linux-based embedded systems, build systems (Yocto, CMake), and cross-compilation toolchains
• Understanding of IoT/vehicle edge environments and field deployment challenges
• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, AI, or related field

Soft Requirements

• Familiarity with multi-camera systems, object re-identification, or behavior/event detection at the edge
• Knowledge of real-time messaging and telemetry systems (MQTT, ZeroMQ, gRPC)
• Experience in public safety, ADAS, surveillance, or vision-based safety-critical applications
• Familiarity with data privacy, security, and compliance for edge AI systems