We are seeking a highly motivated Embedded Resilient AI Engineer Intern to support the evaluation, optimization, and deployment of AI models on resource‑constrained embedded platforms, including FPGA‑based systems and state‑of‑the‑art microcontrollers (MCUs). The intern will work at the intersection of AI performance evaluation, embedded system design, and hardware‑aware AI optimization, with a strong emphasis on robustness, efficiency, and deployability for automotive embedded use cases.

• Evaluate performance of common AI/ML models under embedded constraints (latency, memory, power, accuracy).
• Propose and implement embedded AI solutions suitable for FPGA or MCU platforms
• Deploy and benchmark AI inference on FPGA‑based systems and/or up‑to‑date MCUs.
• Analyze trade‑offs between different hardware platforms and optimization approaches.
• Document results and provide clear technical summaries.