- Location
- Dahlewitz (DE-DW), Germany
- Type
- Part-time
- Department
- IT
- Closing date
- Today
- Source
- Workday
Description
Job Description
Rolls-Royce Deutschland brings together a team of more than 3,500 employees from more than 50 nations, pursuing their passion for excellence when it comes to designing, manufacturing and servicing state-of-the-art aerospace engines.
Our headquarters in Dahlewitz near Berlin are home to the company's Development, Assembly and Customer Service units as well as central administrative and strategic departments.
We deliver the best jet engines in the world. Through intelligent innovation and active collaboration, we're putting our customers at the forefront of the aviation industry and we keep them there. Our product portfolio powers more than 35 types of commercial aircraft, and with over 13,000 engines in-service around the world; we're keeping the world flying. We also offer the possibility to write your thesis and student projects together with Rolls-Royce.
Team accountabilities – How we work:
We are the Digital Manufacturing team and are accountable for operating digital shopfloor systems, driving application development and introducing technology implementation across OE and MRO segments.
Aerospace manufacturing is one of the most complex, high-precision environments in the world. Every component, every process, every anomaly matters and as a matter of fact, most of the data generated today is underutilized.
We are looking for a working student – you will work on building the data foundation and intelligent layers (ML models, AI agents, copilots) that will directly impact how aircraft are built, inspected, and optimized.
This role focuses on building AI and machine learning solutions by preparing and analysing complex operational data to drive efficiency, quality and traceability.
Key accountabilities – What we expect from You:
- Take fragmented, inconsistent manufacturing data (MES, ERP, PLM, IoT) and make it usable, reliable, and model-ready
- Build scalable data pipelines on modern distributed/cloud platforms (preferred tools)
- Identify signal in noisy production environments — defects, drift, inefficiencies
- Build and support ML systems for:
- Predictive maintenance
- Defect detection & root cause analysis
- Process and throughput optimization
- Design and prototype AI agents / copilots that:
- Answer complex manufacturing questions
- Assist in debugging production issues
- Interact with structured + unstructured production data
- Move beyond notebooks – contribute to systems that could actually be used on the shop floor
Qualifications:
- Currently pursuing a Bachelor’s or Master’s degree in Data Science, Computer Science, Mechanical/Electrical/Industrial Engineering or a related field
- Strong programming skills in Python (Pandas, NumPy, and/or PySpark)
- Familiarity with data preprocessing, feature engineering, and large-scale data handling
- Experience with SQL and structured datasets
- Foundational knowledge or project experience in building AI agents, chatbots, or conversational AI systems
- Strong analytical thinking and attention to detail
Pioneer the performance of the future. Join us and you’ll develop your skills and expertise to the very highest levels, working in an international environment for a company known the world over for brilliance and innovation.
Our People are our Power
We are an equal opportunities employer. We’re committed to developing a diverse workforce and an inclusive working environment. We believe that people from different backgrounds and cultures give us different perspectives. And the more perspectives we have, the more successful we’ll be. By building a culture of respect and appreciation, we give everyone who works here the opportunity to realise their full potential.
You can learn more about our global Diversity and Inclusion strategy here
So that you can be your best at work and home, we’ll consider flexible working arrangements for everyone, in any role.
http://careers.rollsroyce.de
Close date: 10.11.2026
Requisition number: JR6162037
Contact: [email protected]