I am a machine learning engineer at CARSYNC GmbH, a provider of connected car solutions in Europe. I have a master's degree in computer engineering from Deggendorf Institute of Technology, where I focused on deep learning and computer vision. My core competencies include machine learning, deep learning, Keras, TensorFlow, OCR, and image processing.

At CARSYNC, I have been working on various projects related to document extraction, such as invoice, vehicle paper, and contract recognition. I have been responsible for training and deploying state-of-the-art deep learning models, such as CNN and RCNN, using Google Colab and AWS. I have also implemented parallel processing and docker-based backend development to optimize the performance and scalability of the models.

I am passionate about applying AI to solve real-world problems and creating value for customers and stakeholders. I enjoy working with a diverse and talented team of engineers and developers, and I am always eager to learn new skills and technologies. I believe that I can bring a unique perspective and experience to the organization, as I have a strong background in both electrical and electronics engineering and computer engineering.