About this job

CHECK24 is the comparison portal: We are both the market leader and a dynamic startup. Working in agile teams, we make fast decisions and embrace flat hierarchies. By leveraging the latest tools and technologies as well as state-of-the-art AI methods, we drive data-driven innovation – always focusing on creating added value for our customers. Across more than 50 products, we work every day to continuously improve the user experience of our more than 20 million customers.

Our Search Team within CHECK24 AI Forge develops scalable AI solutions for search and ranking across different CHECK24 products. Search is a crucial entry and navigation point for our customers and covers challenging domains ranging from e-commerce product search and web-style navigation to travel search for hotels, destinations and other products.

Search and Ranking are among the most demanding disciplines in applied machine learning. A successful system needs to understand user intent, retrieve relevant candidates, rank them effectively and meet demanding requirements for latency, scalability and measurable customer impact.

To strengthen our team, we are looking for someone with first relevant hands-on experience who is eager to grow into a strong Applied Machine Learning Engineer. In this role, you will work on production systems combining classical information retrieval, deep learning, embeddings and Large Language Models and contribute across the entire lifecycle from initial idea and evaluation to deployment, monitoring and continuous improvement.

We look forward to receiving your application as a (Junior) Data Scientist (m/f/d) Search at CHECK24 AI Forge GmbH.

Your profile

• You have successfully completed a degree (typically a Master's) in computer science, mathematics, statistics, physics, electrical engineering or a comparable quantitative field, with strong grades in quantitative subjects
• At least one year of relevant hands-on experience in machine learning or data science is part of your background, including relevant experience gained through working-student positions, internships or your own projects
• Strong Python skills and practical experience with machine-learning or deep-learning frameworks such as PyTorch are part of your technical toolkit
• Solid classical machine-learning skills like gradient boosting, regression and feature engineering are evident in your CV, beyond LLM or RAG applications
• You have practical experience with applications based on Large Language Models, LLM evaluation, tool use or agentic workflows
• A solid understanding of machine-learning fundamentals and systematic model evaluation enables you to assess and improve model performance
• Practical experience with APIs (e.g. FastAPI), containers and Git, ideally a deployed service, complements your interest in building complete production services
• Knowledge of information retrieval, semantic search, recommender systems or learning-to-rank approaches is a plus
• You have English proficiency at C1 level or higher; German is a plus but not required

Your tasks

• You develop and improve machine-learning services for retrieval, ranking, query understanding and classification
• Hybrid search solutions combine lexical retrieval, embeddings, neural models and components based on Large Language Models
• Model development covers training, fine-tuning and systematic evaluation for semantic search, relevance prediction and learning-to-rank use cases
• You create reliable evaluation datasets and metrics and validate improvements through offline evaluations, user signals and A/B tests
• Production-ready services are built from prototypes using technologies such as Python, FastAPI, Docker, PyTorch and vector databases
• Modern AI-assisted and agentic engineering workflows enable efficient prototyping, testing and continuous improvement
• You research promising approaches in information retrieval, recommender systems and Large Language Models and translate them into measurable customer impact

What we offer

Development and responsibility

• Your commitment pays off – we support your talent and provide opportunities to grow your career quickly
• Take ownership of your topics, contribute your own ideas, try new approaches and gradually assume responsibility for production Search and Ranking systems
• Benefit from internal training with specialized coaches as well as an annual budget for external professional development

Team spirit and modern workspace

• Experience team spirit in your daily work and beyond, whether over lunch, a game of table football or after-work activities, and celebrate our successes at regular company and team events
• Work in an inspiring environment with a modern office and high-quality equipment such as MacBooks and height-adjustable desks

Flexibility and balance

• Fridays are home-office optional – and spending them in the office can earn you additional vacation days on top of your 28 days
• Get to the office conveniently with your free Deutschlandticket or a subsidized company bicycle
• Enjoy a free fresh lunch twice a week and use the opportunity to connect with your colleagues
• Stay active with our internal sports classes or take advantage of our subsidized external sports offering, including EGYM Wellpass