Airbus

Internship (d/f/m) in Machine Learning & Multimodal AI

Stellenbeschreibung:

Job Description:

In order to support the Product Data Management department, Airbus Helicopters is looking for an Intern in Machine Learning & Multimodal AI (d/f/m).

Are you looking for an internship and want to help shape the future of automated export control? Then apply now! We look forward to you supporting our team in Donauwörth.

  • Location: Donauwörth
  • Start: As soon as possible
  • Duration: 6 months

Your Location

At our Donauwörth site on the banks of the Danube near Augsburg, we develop helicopters from the initial idea to the flight‑ready product. Experience first‑hand how they take off and land at our own test airfield.

Your benefits

  • Attractive salary and work‑life balance with an 35‑hour week (flexitime)
  • International environment with the opportunity to network globally
  • Work with modern/diversified technologies
  • At Airbus, we see you as a valuable team member and you are not hired to brew coffee, instead you are in close contact with the interfaces and are part of our weekly team meetings
  • Opportunity to participate in the “Generation Airbus Community” to expand your own network

Your Tasks and Responsibilities

  • Research & Benchmarking: Analyze current ML models (TF‑IDF/Random Forest) in comparison to state‑of‑the‑art Deep Learning and LLM architectures
  • Multimodal Development: Design and prototype models that process text as well as technical drawings and metadata
  • Performance Optimization: Define metrics to increase accuracy in identifying export control sensitivities
  • Prototyping: Implement Proof‑of‑Concepts (PoC) and integrate them into the existing AI tool
  • Cross‑functional Collaboration: Coordinate with Data Scientists, Engineers, and Legal Experts to ensure regulatory compliance

Desired skills and qualifications

  • Enrolled full‑time student (d/f/m) in Computer Science, Data Science, Mathematics, Physics, or a comparable field of study
  • Knowledge of Machine Learning (Scikit‑learn) and Deep Learning frameworks (e.g., PyTorch, TensorFlow)
  • Experience with NLP, LLMs, and ideally Computer Vision (OCR/image processing)
  • Strong analytical skills and a proactive approach to work within a regulated environment
  • Proficient English skills (negotiation level); German knowledge is an advantage

Please upload the following documents: cover letter, CV, relevant transcripts, enrolment certificate, study regulation.

Not a 100% match? No worries! Airbus supports your personal growth.

Take your career to a new level and apply online now!

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company: AIRBUS HELICOPTERS DEUTSCHLAND GmbH

Employment Type: Internship

Experience Level: Student

Job Family: Digital

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.

Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

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Stelleninformationen

  • Veröffentlichungsdatum:

    12 Mär 2026
  • Standort:

    Donauwörth

    Einsatzort:

    Airbus Defence and Space GmbH
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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