EMBEDDED SOFTWARE ENGINEER

Description

Job Summary: We are seeking an Embedded AI Engineer to design and develop advanced artificial vision and deep learning algorithms for mobility solutions. Key Highlights: 1. Design and development of artificial vision and deep learning algorithms. 2. Optimization of AI models for various hardware platforms. 3. Collaboration on the integration of software and hardware solutions. **Description:** ---------------- At Eysa, we are leaders in urban and interurban mobility solutions. This time, we are looking for an Embedded AI Engineer with strong C\+\+ experience and who has also worked with: * NPU/FPGA-based platforms * TFlite/onnx/TensorRT * Linux-based development * Industrial embedded systems It is a plus if you bring: * Experience in OCR or similar is desirable * Experience in the traffic sector is a plus What will you do on a daily basis? Design and develop advanced artificial vision and deep learning algorithms tailored for industrial and traffic environments. Prototype, evaluate, and integrate new AI models into video analytics-oriented solutions. Optimize models for execution across different hardware platforms (GPU, FPGA, CPU, embedded systems). Analyze requirements and propose efficient, scalable technical architectures. Collaborate with software and hardware teams on solution integration. Participate in continuous improvement of training, validation, and deployment tools. Document processes, conduct performance analysis, and recommend technical improvements. WE OFFER: Hybrid work model at our offices in Alcobendas or Barcelona, with flexible working arrangements. Salary starting from €65k At our company, we promote equal opportunities: we firmly believe diversity is a source of talent and growth. Therefore, we foster an inclusive environment where respect, belonging, and commitment are essential values. We invite all individuals to join our team, regardless of origin, personal circumstances, experience, or condition—don’t hesitate; apply so we can get to know you. **Requirements:** --------------- * NPU/FPGA-based platforms * TFlite/onnx/TensorRT * Linux-based development * Industrial embedded systems