Bachelor's / Master's Thesis - Applied AI: Machine Learning & AI Agents (m|w|d)

idealo internet GmbH
Berlin, Germany
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
German
Job source

Tech stack

Artificial Intelligence Computer Engineering Python (Programming Language) Machine Learning NumPy Pytorch Pandas Scikit Learn Information Technology

Job description

  • And what about the office? Our office in the heart of Berlin offers free organic breakfast, excellent free lunch (vegan and vegetarian), as well as free coffee, lemonades and after-work beer, in addition to the ā€œstandard foosballā€. It also has a fabulous rooftop terrace with view of the whole of berlin where you can network with colleagues from our group of companies.
  • In need of additional support in any areas of your life? We offer free counseling and support in all areas of life (professional, private, family, health, etc.) in cooperation with the pme-Familienservice.
  • Want to keep yourself fit? We offer many different fitness and sports options, such as an Urban Sports or Gympass membership, to suit your personal needs.
  • And what else is there? Of course, success must be celebrated! In addition to team events, you can also expect big company events and other moments of organized connection with others in the company and your team throughout the year!

Requirements

  • You are studying Computer Science, Computer Engineering, Data Science, Mathematics, Information Technology, or a related STEM field, ideally with a focus on Machine Learning or Artificial Intelligence.
  • You are enrolled at a German university, will remain enrolled for at least another 12 months, and can arrange academic supervision for your thesis at your university.
  • You have a solid theoretical understanding of Machine Learning and Deep Learning, along with good Python programming skills and experience with libraries such as scikit-learn, pandas, NumPy, or PyTorch.
  • You take ownership and independently drive topics forward.

  • You enjoy tackling challenges actively and solving them pragmatically.

About the company

Bachelor’s / Master’s Thesis - Applied AI: Machine Learning & AI Agents (m w d)

idealo internet GmbH Zimmerstrasse 50 c/o Schützenstraße 15-17, Berlin, 10117 Teilzeit

Automatically cataloging more than 2 billion offers from over 50,000 online shops is a complex challenge that requires intelligent and scalable machine learning solutions. At idealo, our team working on offer recognition and catalog association is responsible for this process, which forms a central part of our price comparison platform.

We develop and apply modern machine learning methods, explore the potential of Large Language Models and agentic AI systems, and ensure our ML systems operate reliably and at scale in the cloud. From researching and evaluating new approaches to MLOps and production-ready ML systems, we combine scientific research with real-world engineering challenges.

As part of your Bachelor’s or Master’s thesis, you’ll have the opportunity to contribute your own ideas, experiment with emerging technologies, and explore machine learning solutions using real-world e-commerce data. You’ll be supported by experienced software engineers with academic backgrounds and extensive experience supervising scientific research projects. This gives you the chance to connect academic research with practical challenges at one of Germany’s largest price comparison platforms.

About your new role

  • AI Agents: You research and develop agentic AI systems for automatically recognizing, processing, and cataloging product offers.
  • Foundation Models: You explore how Foundation Models and Large Language Models can be applied to product classification in e-commerce.
  • Machine Learning Development: You develop ML solutions in Python using frameworks and technologies such as PyTorch, AWS Strands, and AWS Bedrock in a cloud-based environment.
  • Scientific Research: You investigate current scientific approaches, develop your own ideas, and evaluate them using real-world datasets and use cases.
  • Practical Application: You explore how your approaches can improve automated offer cataloging while considering the requirements of scalable, production-ready ML systems.

Apply for this position

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