Machine Learning Scientist II - Recommendation Applications ML / Marketplace

About Us: At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world. Role Description: This role is based in Amsterdam. Booking.com's Marketplace Department turns travel goals into travel realities. Our purpose? To create frictionless experiences at each and every stage of the trip. From browsing to booking and beyond, our focus is on building the connected experiences which make journeys smoother, faster and more enjoyable. Think of us as travel matchmakers, ensuring seamless integration across our product verticals to effortlessly and intuitively connect traveler preferences and actions. The Recommendation Applications ML team is dedicated to enhancing the overall customer experience and user journey. The team’s mission is to be the centralized hub for all machine learning (ML) recommendation initiatives, providing scalable, reusable, state-of-the-art ML models. These models aim to increase relevance and personalization, enabling customers to be context-aware and make quicker, more informed decisions. Our team supports the vision of making travelers feel understood and assisted in every step of the travel booking journey. In 2025, we are planning to focus on expanding and optimizing our recommendation systems, for example by improving personalization and leveraging GenAI to build fine-tuned models for more relevant recommendations. As a Machine Learning Scientist, you will be developing state-of-the-art Machine Learning models, owning the design and delivery of ML systems, from initial idea-generation, collecting business requirements from product stakeholders to implementation. You will work closely together with the other Machine Learning Scientists and Machine Learnings Engineers in the Intent Discovery track as well as with Data Engineers, Software Engineers and Product Managers. Key Job Responsibilities and Duties: Work in a multi-disciplined team where you’ll take full ownership of turning discoveries and ideas into products through machine learning (incl. understanding product requirements, data discovery, model development and evaluation, to implementation of a full production pipeline for both batch and stream-based deployment). Use the ML model’s output to deliver both short-term commercial impact and longer-term differentiated business value and customer experience. Define and build proof-of-concepts to test new ideas and demonstrate their potential value to relevant stakeholders. Develop production-grade ML code for models, features, and pipelines, accounting for scalability, latency, realtime requirements, monitoring and retraining. Build readable and reusable code, using the right technologies and coding methodologies applying knowledge of business area tools and product needs. Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies, and upskilling on these as needed. Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, interviewing, onboarding and mentoring colleagues. Qualifications & Skills: Masters, PhD, or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.). At least 3 years of relevant work experience. Experience with TensorFlow/PyTorch is a strong plus. Solid understanding of fundamental machine learning concepts. Fluency in at least one programming language, with a strong preference for Python. Strong working knowledge of Spark and SQL. Experience with experimental design, A/B testing, and evaluation metrics for ML models. Excellent communication and collaboration skills to work effectively with diverse crafts such as engineering, UX, and product management. Experience working on complex multi-stage recommender architectures is a strong plus. Benefits & Perks - Global Impact, Personal Relevance: Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive compensation and benefits package, as well unique-to-Booking.com benefits which include: Annual paid time off and generous paid leave scheme including: parental (22-weeks paid leave), grandparent, bereavement, and care leave Hybrid working including flexible working arrangements, working from home furniture and ergonomic support, and up to 20 days per year working from abroad (home country) A beautiful sustainable HQ Campus in Amsterdam, that offers on-site meals, coffee, and snacks, multi-faith and breastfeeding rooms at the office* Commuting allowance and bike reimbursement scheme Discounts & Wallet credits to spend on our products, upgrade to Booking.com Genius Level 3, and friends & family Booking.com discount vouchers Free access to online learning platforms, development and mentorship programs Global Employee Assistance Program, free Headspace membership Diversity, Equity and Inclusion (DEI) at Booking.com: Diversity, Equity & Inclusion have been a core part of our company culture since day one. This ongoing journey starts with our very own employees, who represent over 140 nationalities and a wide range of ethnic and social backgrounds, genders and sexual orientations. Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just build an outstanding workplace, it also creates a better and more inclusive travel experience for everyone. Inclusion is at the heart of everything we do. It’s a place where you can make your mark and have a real impact in travel and tech.” We ensure that colleagues with disabilities are provided the adjustments and tools they need to participate in the job application and interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Application Process Let’s go places together: How we Hire The interview process entails: 1. "On the spot" Business Case Interview, 2. "Take home" Business case Interview, 3. Final behavioral interview This role does not come with relocation assistance. Booking.com is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive. Pre-Employment Screening If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.