Intern (f/m/d) Data Analysis & Machine Learning Software Engineer - Flight Safety

About Rocket Factory Augsburg

At Rocket Factory Augsburg (RFA) we have one goal: create low-cost, flexible and reliable access to space. We specialize in the creation of small launcher solutions designed for deploying satellites into Low Earth Orbit (LEO) and beyond. Together with you, we want to revolutionize space services and help enhance life on Earth. Sounds interesting? Then join our journey and be part of the team leading the New Space movement in Europe!

About the Team

Our Flight Safety team is seeking a motivated intern for a minimum 5-month mandatory university placement (40+ hours/week) to support the integration of machine learning into our operational workflows. This is a highly data‑centric role focused on the design, construction, and maintenance of a robust data infrastructure capable of storing and processing large volumes of time‑series data including rocket and debris trajectories.

In addition to raw trajectory data, the datasets include a wide range of derived and interrelated quantities: trajectory metadata, fragment properties, and safety‑relevant metrics. Ensuring consistent data management, efficient storage, and reliable access is critical both for downstream machine learning models and for integration with other engineering tools. A solid understanding of the underlying physics of trajectories is highly desirable, as it enables the development of meaningful, physically informed features for ML applications.

Responsibilities

• Manage and optimize a hybrid database system for scalable storage and efficient querying of large‑scale time‑series data
• Configure and run data generation and processing pipelines using CI/CD practices
• Extend and maintain software systems that interface with other departments, ensuring data consistency and interoperability
• Pre‑process, analyse, and post‑process complex simulation outputs, including trajectory and fragmentation data
• Design and implement machine learning models to optimize parameters affecting flight safety and operations
• Visualise complex, multi‑dimensional datasets using clear, intuitive, and interactive plots with proficiency in Matplotlib, Seaborn, or Plotly as a strong advantage

Qualifications

• Currently enrolled in a university program for the duration of the internship
• Pursuing a Master’s degree in Computer Science, Engineering, Mathematics, or equivalent; or 2+ years of professional software development experience in lieu of a degree
• Strong proficiency in Python and associated data science libraries
• Demonstrated experience with large datasets, including HDF5, Parquet, or Feather for efficient storage and I/O
• Experience using SQL databases (e.g., PostgreSQL, MySQL) for managing structured relational data, including schema design, query optimisation, and integration with data pipelines
• Fluent in written and spoken English as all day‑to‑day activities and documentation are conducted in English
• Highly motivated to independently learn about the following:
  • Creating dockerfiles and managing docker services with docker‑compose
  • Setting up CI/CD jobs using gitlab’s YAML syntax
  • Optimization of data storage formats for size and/or read speeds
  • Linux server management – configuration files, cron jobs, performance monitoring

Benefits

• Atmosphere: Experience life in an international & dynamic New Space start‑up
• Flexibility: Fit your working schedule to your needs with flexible working hours
• Health: Sweat, stretch or squat it out with EGYM Wellpass
• Paid Time Off: 20 days annual leave and special leave days
• RFA Family: Join regular company and team events
• Parking: Free parking for car and bike