Requirements •Currently enrolled in a Master's or PhD program, preferably in Mechanical Engineering, Industrial Engineering, Automation, Computer Science, or related fields •Proficient in Python programming, RPA and familiar with mainstream machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) •Genuine interest in applying AI technologies in manufacturing or production environments; relevant project experience is a plus •Basic data processing and analysis skills (e.g., SQL, Pandas, NumPy) •Strong logical thinking and problem-solving abilities, capable of independently handling small project modules •Good cross-team communication skills, able to collaborate effectively with engineers and production managers •Fluent in English (both written and spoken) for technical document reading and basic communication Responsibilities •Participate in an AI project in the Engine Logistics with the developers and line feeding team. The project goal is to develop one AI method to train an AI model to predict and validate the engine line feeding. •Assist in collecting and analyzing line feeding and picking process data to support model training and validation •Track result from the proof-of-concept and propose further model improvements •Support model training with unstructured data, such as AI glasses and picking states Support creation of dashboards or reports for visualization that can enhance model insight and usability •Present findings regularly to the project team and contribute to the long-term AI roadmap •Help organize internal AI tech sharing sessions or training activities to promote team capability building •Document methodologies, results, and recommendations for future industrialization