Embedded AI Engineering Intern [IDA:00058]
Summary
The Embedded AI Engineering Intern will evaluate, implement, and benchmark AI/ML models on embedded hardware platforms like FPGAs and MCUs. The role focuses on optimizing model performance for latency, memory, and power constraints within the mobility sector.
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.
1. Bachelor’s or Master’s student in Electrical Engineering, Computer Engineering, Computer Science, or related field.
2. Programming experience in C/C++; Python is a plus.
3.Basic understanding of machine learning and embedded systems.
Interest or exposure to FPGA or MCU-based AI acceleration.
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