Embedded AI Engineering Intern

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.

1.Evaluate performance of common AI/ML models under embedded constraints (latency, memory, power, accuracy).

2.Propose and implement embedded AI solutions suitable for FPGA or MCU platforms
3.Deploy and benchmark AI inference on FPGA-based systems and/or up-to-date MCUs.
4.Analyze trade-offs between different hardware platforms and optimization approaches.
5.Document results and provide clear technical summaries.