Responsibilities may include: Develop, test and optimize embedded software modules for AI-based automative applications (e.G. perception, decision-making, sensor fusion). Collaborate with cross-functional teams including hardware engineers, data scientists, and system architects. Implement and validate machine learning models on embedded platforms (ARM Cortex or automotive-grade SoCs). Assist in profiling and optimizing code for performance, memory usage, and power efficiency. Support integration of AI algorithms into real-time automotive systems. Document development processes, test results, and technical findings. Qualifications: Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or related field. Strong programming skills in C/C++ and Python. Familiarity with embedded systems development and real-time operating systems (RTOS). Basic understanding of AI/ML concepts and frameworks (e.G. TensorFlow Lite, PyTorch Mobile). Experience with version control systems (e.G. Git). Good problem-solving skills and ability to work in a collaborative environment. Preferred Qualifications: Experience with automotive communication protocols (CAN, LIN, Ethernet). Exposure to model deployment on edge devices or embedded AI accelerators. Familiarity with tools like MATLAB/Simulink, ROS, or OpenCV