Existing use case sustenance: establish performance monitoring metric for deploy AI models to ensure accuracy and reliability in production environments. Identify potential issues or deviations and implement necessary adjustments such as re-training or model fine-tuning Enhance AI workflows: Refine datasets and improve data preprocessing pipelines to ensure robust model performance Evaluate and validate models: benchmark AI models against KPIs and validate model outputs to ensure adherence to business requirements and mitigate risks Collaboration and knowledge-sharing: work closely with cross-functional teams to sustain current AI applications and align with business needs Research and development: explore & suggest tools, techniques and technologies to further improve model performance Support scaling effort: contribute to the deployment and scaling of AI models across processes and sites On track to attaining Masters/Bachelors/Diploma in Natural Science, Computer Science, Data Science, Statistics, Mathematics, or equivalent fields Preferably able to commit to internship period of Mar 26 - Aug 26 Basic to intermediate knowledge of machine learning and image classification techniques (e.g., CNNs, transfer learning, etc.) Familiarity with tools such as Python, TensorFlow, PyTorch, or similar machine learning frameworks Experience with image processing libraries like OpenCV, Pillow, or scikit-image is a plus Familiarity with any version control system (e.g., Git) and cloud platforms (e.g., AWS, Azure, or Google Cloud) is a bonus We are on a journey to create the best Infineon for everyone. This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills.
