Public summary
An internship opportunity focused on enhancing machine learning models for predictive reliability analytics in heat pumps. The role involves data preparation, feature engineering, model evaluation, and applying generative AI to generate reports. The position offers hybrid work in Wernau and requires English proficiency and ongoing enrollment in a relevant master's program.
Location and work setup
- Location
- Wernau (Neckar)
- Remote status
- Hybrid
- German requirement signal
- No German Required Detected
- Detected job language
- English
Responsibilities
Contribute to reviewing and enhancing data preparation and feature engineering methods. Support optimization and evaluation of machine learning models. Investigate new features and early risk indicators in IoT and field data. Develop reproducible ML workflows using Databricks and MLflow. Adapt existing approaches to other product reliability use cases. Explore Generative AI applications to transform model outputs into clear reports. Communicate findings through visualizations, presentations, and documentation.
Qualifications
Currently enrolled in a master's program in Data Science, Artificial Intelligence, Computer Science, Information Systems, Engineering or related fields. Practical experience with machine learning concepts including model evaluation, feature engineering, and data preprocessing. Proficient in Python. Experience with Databricks, MLflow, PySpark, or Generative AI is advantageous. Strong independent work ethic, organizational skills, and clear technical communication. Fluent in English.