Embedded Systems Engineering Student | AI & Low-Level Development
🎓 Master's in Embedded Systems Software @ Université de Bretagne Occidentale (Brest, France)
🔍 Looking for a 6-month internship starting March 2026 in Embedded AI / Edge AI
I'm passionate about safety-critical systems where reliability and performance are essential. My expertise lies at the intersection of low-level systems programming and embedded machine learning — I enjoy the challenge of deploying AI models under real hardware and real-time constraints.
Currently completing my Master's degree with hands-on experience in:
- Linux kernel development (drivers, synchronization, device management)
- Embedded ML optimization (quantization, edge deployment, MLOps)
- Real-time systems (RTOS, protocols, hardware interfaces)
Publisher/Subscriber communication driver for Linux kernel
- Character device implementation with ioctl support
- Multi-client management (publishers/subscribers)
- Synchronization mechanisms (mutex, spinlocks)
- FIFO message queue with complete test coverage
Tech: C Linux Kernel Device Drivers Concurrency
Systematic empirical study of backdoor attacks on convolutional neural networks
- 27 experimental configurations with 88-96% attack success rate
- Full MLOps tracking with Weights & Biases
- Statistical validation across multiple architectures
Tech: Python PyTorch MLOps W&B
Android application using AI to detect driver drowsiness in real-time
- Google ML Kit integration with <50ms response time
- Developed during Erasmus exchange in Finland
- Awarded grant from University of Oulu
Tech: Kotlin Android Google ML Kit Mobile AI
Languages
Embedded Systems
AI / ML
Tools & DevOps
Open to opportunities in Embedded AI, Edge Computing, and Safety-Critical Systems across Europe.