Machine Learning Engineer I

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.

The team:
Supplier Integrity Product is part of Booking.com’s Supplier Fraud organisation. Our mission is to keep Booking.com’s accommodation supply trustworthy and economically healthy by detecting, preventing, and remediating partner-side integrity issues such as commission avoidance, fake reviews, bait-and-switch, collusion, and other abusive behaviours.

Role Description:
As a Machine Learning Engineer at Booking.com, your work will focus on training and deploying machine learning models (Classification, Deep Learning, Optimization, Natural Language Processing, Active Learning) using the most advanced technologies and models. You will be responsible for identifying and using the most appropriate data sources and modeling techniques to solve complex problems and drive measurable business value.

You will also help in building new products and solutions by driving a research agenda and development plan from ideation to prototyping to full productionisation in the team, and using opportunities to contribute to a vibrant department’s ML community.

Key Job Responsibilities and Duties:

• Develop production-ready ML systems, focusing on models, features, and pipelines, with a focus on reliability and scalability.
• Collaborate with others to monitor the health and performance of systems, with guidance from senior engineers.
• Assist in business-related data governance processes, including technical implementation and maintenance of data processing services and storage systems.
• Evaluate possible architecture solutions taking into account business and technology requirements.
• Set relevant service level objectives SLOs and contribute to achieving them.
• Build readable and reusable code, using the right technologies and coding methodologies, applying knowledge of tools and product needs.
• Stay up-to-date with the latest developments in ML/AI and related technologies, as well as upskill on these topics as needed.
• Participate in internal ML programs and share knowledge with others through clear communication.
• Apply a cross-disciplinary perspective to solve issues by considering approaches and methods from various disciplines.
• Achieve mutually agreeable solutions by staying adaptable, communicating ideas clearly, and practicing active listening.

Qualifications & Skills:

• 1+ years of relevant work experience (or equivalent), involved in applying Machine Learning to business problems in a commercial environment.
• Experience with the Fraud domain is a plus.
• Experience in areas like e.g. PySpark, Airflow, Snowflake, AWS SageMaker, Recommender Systems, Deep Learning, Information Retrieval, Causal Inference, MLOps, etc.
• Work experience (or equivalent) involved with the application of Machine Learning to business problems, preferably in a commercial environment.
• Knowledge of multiple machine learning facets, such as working with large data sets and experimentation. Experience with data-driven product development: analytics, A/B testing, etc.
• Strong working experience in one or more general purpose programming languages (Preferably Python).
• Experience of version control systems.

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: parent, grandparent, bereavement, and care leave
• Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country)
• Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit
• Living and working in Amsterdam, one of the most cosmopolitan cities in Europe
• Contributing to a high scale, complex, world renowned product and seeing real-time impact of your work on millions of travelers worldwide
• Working in a fast-paced and performance driven culture
• Opportunity to utilize technical expertise, leadership capabilities and entrepreneurial spirit
• Promote and drive impactful and innovative engineering solutions
• Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences and active community participation
• Competitive compensation and benefits package and some great added perks of working in the home city of Booking.com

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:
This section should provide:

• Let’s go places together: How we Hire
• 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.

Key Skills
Recommender Systems, Deep Learning, Information Retrieval, Computer Vision, Speech Recognition, Causal Inference, MLOps, Python, SQL, PyTorch, Spark, Snowflake

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.