Internship in Digitalization for Machine Learning (all genders)

Big tasks

• Development, implementation and optimization of machine learning models at the proof-of-concept level
• Scaling of machine learning models for use in production systems, taking into account performance, scalability and security.
• Design, testing and management of data pipelines for training and production systems
• Data acquisition, quality assurance, and feature engineering
• Close and independent collaboration with data scientists, software developers and other teams to integrate models into existing workflows
• Research, evaluation and selection of suitable machine learning algorithms and technologies, based on current research findings
• Target-group-oriented documentation and presentation of the developed models and their results

Ideal conditions

• Studies in Computer Science, Computer Engineering, Mathematics, Statistics, Engineering or a comparable field of study
• Relevant experience in the development and implementation of machine learning models, preferably in computer vision projects, and sound knowledge of Python.
• Experience with machine learning tools such as PyTorch and Scikit-learn
• Knowledge of working with large datasets and database technologies
• Prior experience in API development and the integration of ML models into production environments, as well as experience with production technologies and tools (Docker, Kubernetes, GitHub, VSCode, Linux) is desirable.
• Very good German and English skills
• Strong analytical skills and the ability to communicate complex relationships in an understandable way.
• Teamwork skills and a proactive, independent work style

Excellent environment

• Practical insights into the aviation industry and jobs with responsibility
• Strong team cohesion, partly through our student network and various events.
• Individual support through mentoring and dedicated contact persons
• Flexible working hours and the possibility of mobile working (depending on the area of ​​work)
• Delicious and varied dishes in our company cafeteria
• EGYM Wellpass and opportunity to participate in local running events