Embedded AI Engineer

Your job:

• Develop, optimize, and deploy machine learning models for embedded and edge devices
• Ensure real-time performance, memory efficiency, and low-power operation of on-device AI solutions
• Integrate ML algorithms with microcontrollers, embedded controllers, and edge computing platforms
• Implement pipelines for model conversion, quantization, and hardware acceleration
• Collaborate with software, controls, and hardware engineers to deliver production-grade embedded AI systems
• Participate in prototyping, testing, benchmarking, and continuous improvement of embedded AI solutions
• Work with the global research teams to translate concepts into scalable prototypes for industrial automation

Your qualification:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Electronics, or related field
• 2–5 years of hands-on experience in Embedded Systems and AI/ML development
• Strong programming proficiency in Python, C/C++, and embedded development
• Practical experiencewith embedded ML frameworks such as TensorFlow Lite, ONNX Runtime, Edge Impulse, or similar
• Solid understanding of real-time embedded systems, microcontroller architectures, and communication protocols
• Experience with model optimization techniques (quantization, pruning, hardware-specific acceleration) is a plus
• Familiarity with edge hardware platforms such as ARM Cortex, STM32, ESP32, NVIDIA Jetson, or similar is desirable
• Ability to work in a fast-paced research-driven environment with strong ownership and autonomy