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Student Assistant as AI & ML Engineer

Fraunhofer-Gesellschaft

Berlin

Vor Ort

Teilzeit

Vor 25 Tagen

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Zusammenfassung

A renowned research institute in Berlin is seeking a Working Student as AI & ML Engineer. You will develop deep learning models and build data pipelines to enhance an AI-powered design platform for residential construction. Candidates should have a strong grasp of Python and relevant frameworks. This role offers flexible working hours, a modern workspace, and the opportunity to tackle fascinating challenges in a scientific and entrepreneurial environment.

Leistungen

Attractive salary
Modern workspace
Flexible working hours
Opportunities to work from home
Cooperative working atmosphere

Qualifikationen

  • Currently enrolled student at a university in Berlin or Brandenburg.
  • Solid knowledge of Python and experience with PyTorch.
  • Familiar with GPU workflows and distributed training setups.
  • Experience in data handling with NumPy and Pandas.
  • Able to troubleshoot training and inference issues.
  • Enthusiastic team player with clear communication skills.
  • Capable of turning research insights into code.
  • Willingness to work on-site at least 3 days per week.

Aufgaben

  • Develop deep learning models for 2D floor plans.
  • Build data pipelines from architectural drawings.
  • Apply mathematical and analytical thinking to complex challenges.
  • Develop and optimize performance of tools and prototypes.
  • Test new methods and contribute to product improvements.

Kenntnisse

Python
Deep learning frameworks (PyTorch)
GPU workflows
Data preprocessing and augmentation
Analytical thinking
Team collaboration
Research mindset
Fluent in English

Ausbildung

B.Sc./M.Sc. in Computer Science, Machine Learning, Data Science or related field
Jobbeschreibung
Future. Discover. Together.

If you are passionate about start-ups, we are delighted to present this fantastic opportunity at HHI. Our vision? To accelerate the emergence of groundbreaking, technology-driven start-ups. To do this, we rely on talents like YOU – with a mix of deep tech projects, financial support, professional premises, and a strong network of mentors and coaches. Become part of our team and join us on a journey of research and innovation!

As part of our project with the startup D3Companion, we are looking for a Working Student as AI & ML Engineer (m/f/d).

In cooperation with the startup D3Companion, an AI-powered design platform for residential construction is being developed. It enables architects and planners to implement building designs significantly faster and more efficiently by combining generative design, automated floor plan creation, comprehensive performance analyses, and seamless BIM integration in a single solution.

Be part of change
  • Develop models: Design and train deep learning models (CNNs, GNNs) for creating 2D floor plans
  • Prepare data: Build our data pipelines – from reading architectural drawings to preprocessing and augmentation, all the way to labeling and versioning
  • Solve problems: Apply mathematical and analytical thinking to tackle complex spatial and geometric challenges
  • Write clean code: Develop reliable, well-structured code and optimize the performance of our tools and prototypes
  • Research & experiment: Test new methods, run experiments, and contribute ideas that improve our models and products
What you contribute
  • You are currently a student (B.Sc./M.Sc.) in Computer Science, Machine Learning, Data Science, or a related field at a university in Berlin or Brandenburg
  • Python expert: Solid knowledge of Python and practical experience with PyTorch or similar deep learning frameworks
  • GPU know-how: Familiar with GPU workflows and distributed training setups
  • Data competence: Experience in preprocessing, augmentation, and dataset organization; confident with NumPy and Pandas
  • Analytical & solution-oriented: Able to identify and fix issues in training and inference pipelines
  • Team player: Clear communication skills and enthusiasm for collaboration in a dynamic startup environment
  • Research mindset: You read papers, reproduce experiments, and turn insights into working code
  • Fluent in English (German is a plus, but not required)
  • Willingness to work on-site at least 3 days per week at the Fraunhofer HHI Accelerator, Silicon Allee (Berlin)
What we offer
  • Fascinating challenges in a scientific and entrepreneurial setting
  • Attractive salary
  • Modern and excellently equipped workspace in central location
  • Great and cooperative working atmosphere in an international team
  • Flexible working hours
  • Opportunities to work from home

The position is initially limited to one year. An extension is explicitly desired.

The monthly working time is 80 hours. This position is also available on a part-time basis. We value and promote the diversity of our employees' skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable – for applicants with disabilities, we work together to find solutions that best promote their abilities. The same applies if they do not meet all the profile requirements due to a disability.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

Ready for a change? Then apply now and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next.

Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute HHI

www.hhi.fraunhofer.de

Requisition Number: 82149 Application Deadline: 12/15/2025

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