Embedded AI Engineer

Job Summary

To support the advancement of intelligent edge computing, the full-time Embedded AI Engineer will lead the development and deployment of deep learning models on IoT platforms, focusing on optimizing computer vision models for execution on high-efficiency hardware accelerators in a hybrid work environment.

Key Responsibilities

• Develop and optimize embedded software and AI model inference pipelines for real-time object detection, tracking, and classification at the edge
• Deploy and maintain vision-based deep learning models on resource-constrained devices using AI accelerators
• Collaborate with AI/ML researchers to integrate trained models into embedded applications and validate edge inference accuracy

Required Qualifications

• Proficient in C/C++ and Python for embedded development and AI integration
• Hands-on experience with at least one AI hardware platform such as Hailo or NVIDIA Jetson
• Solid understanding of deep learning architectures and model behavior, including CNNs and YOLO
• Experience working with Linux-based embedded systems and build systems like Yocto
• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, AI, or a related technical field