About the role
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.
Skills & 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.
At idealo you can expect
You want to further your education? We take your personal development goals seriously and, in addition to our idealo Learning Hub, eLearning offerings (e.g., Udemy), coaching & mediation, we also offer you the opportunity to benefit individually from additional learning and development budget.
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 "standard foosball". 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.
You want full flexibility on your way to work and beyond? No problem with a job bike or Deutschlandticket - and it's environmentally friendly, too!
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!
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