Machine Learning Scientist II

About Us:

At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. Through our products, partners and people, we make it easier for everyone to experience the world.

About the team:

The Booking Ads ML team builds Machine Learning solutions that power Ads across Booking.com, enabling partners to reach the right travellers at the right moment while preserving customer experience and conversion. Based in Amsterdam, the team works cross-functionally with Data Science & Analytics and Data Engineering, and closely with Product and Engineering, to tackle large-scale, high-impact problems using advanced ML on complex data. As part of a fast-growing domain, the team plays a key role in scaling the Ads business and shaping how advertising integrates seamlessly into the Booking.com platform.

As an ML Scientist II in the Booking Ads ML team, you will design, build, and improve Machine Learning models that drive Ads use cases across Booking.com. You will work on problems such as ad relevance, ranking, and performance optimization, applying strong ML fundamentals to large-scale, real-world data. In close collaboration with Product, Engineering, DS&A, and Data Engineering, you will contribute production-ready models, iterate based on experimentation and business feedback, and help evolve shared ML codebases and tooling.

Key Responsibilities

• Work in a multi-disciplinary team where you’ll take full ownership of turning discoveries and ideas into products through Machine Learning (including understanding product requirements, data discovery, model development and evaluation, to implementation of a full production pipeline for both batch and stream-based deployments).
• 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:

• At least 4 years of relevant work experience. Experience in ranking, recommender systems, personalization, e-commerce, etc. is a plus.
• Masters, PhD, or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.).
• We prefer candidates with Deep Learning experience, especially when applied to large-scale datasets or sequential modelling. Experience with TensorFlow or PyTorch is a plus.
• Solid understanding of fundamental machine learning concepts, such as gradient boosting, neural networks, feature engineering, model evaluation, etc.
• Fluency in at least one programming language, with a strong preference for Python.
• Strong working knowledge of Spark and SQL.
• Experience with putting Machine Learning models in production is a plus.
• Excellent English communication skills, both written and verbal; the ability to convey your message to team members and other stakeholders.

Benefits & Perks - Global Impact, Personal Relevance:

• 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

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.