About trivago
When travelers are searching for a hotel, we want the obvious choice to be trivago! Our leading metasearch engine is super fast and constantly optimized - enabling millions of travelers to compare hotel prices from hundreds of booking sites and find great deals in just a few clicks. We use cutting-edge technology, real-time auction, and machine learning techniques with petabytes of data to create an experience that saves travelers time and money. In the lively city of Düsseldorf, we seize opportunities to learn everyday, innovate, and make an enduring mark on the travel industry. At trivago you will find those who aren't afraid of change but rather embrace it, turning every challenge into a pathway for growth. Join trivago, work with a great team, and grow with us!
Responsibilities
- Analyze large datasets to unearth hidden patterns and share actionable insights that inform strategic decisions about search quality and user behavior
- Build and productionize algorithms using advanced techniques such as predictive modeling, statistical modeling, machine learning, or deep learning to solve complex search and ranking challenges
- Design and implement scalable search architectures integrating semantic retrieval, query understanding, and Learning-to-Rank algorithms with production-ready performance
- Drive the implementation of ML solutions end-to-end, from concept to production deployment, ensuring robustness and reliability at scale
- Perform quality checks for the work of less experienced data scientists, provide constructive feedback, and share knowledge and best practices across the unit
- Collaborate with cross-functional partners including engineers, product managers, and stakeholders to deliver ML systems that impact millions of travelers
Requirements
- 5+ years of experience in search, information retrieval, NLP, machine learning, or deep learning with demonstrated product impact
- Deep expertise in semantic search technologies including query understanding, embedding-based retrieval with vector databases, and Learning-to-Rank methodologies
- Proficiency with LLMs and transformer architectures (BERT, T5, GPT) including fine-tuning, prompt engineering, and application to search use cases
- Strong Python and SQL skills with hands-on experience using ML frameworks such as PyTorch, TensorFlow, or HuggingFace
- Solid foundation in statistics with proven ability to design, execute, and analyze large-scale A/B tests and apply causal inference methods
- Excellent communication and collaboration skills with the ability to explain complex ideas to non-technical stakeholders and mentor junior team members
- Masters or PhD in Computer Science, Machine Learning, Information Retrieval, Natural Language Processing, Recommender Systems, or a closely related field
Benefits
- Personalized coaching and development opportunities through Nilo
- Workshops, educational meetups, conferences, free online learning courses, and access to a fully-equipped campus library
- Visa support, relocation package, interest-free newcomer loan, free language classes
- Flexible working hours, up to 2 work from home days weekly, remote work from Germany or selected countries abroad for up to 20 days per year
- Self-determined vacation (minimum of 25 days)
- Free access to the Heycare platform for personalized nanny assistance and on-campus kids room
- Complimentary snacks and drinks, on-site gym, sports classes, and Urban Sports Club membership