Machine Learning Engineer - Customer Services

Machine Learning Engineer - Customer Services 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: We are seeking a highly skilled Machine Learning Engineer to join our CS Decision Intelligence product team. In this role, you will develop, deploy, and maintain machine learning models that enhance customer service efficiency and productivity through AI-driven solutions. You will collaborate closely with data scientists, product managers, and other stakeholders to integrate and scale ML solutions that impact millions of customers worldwide. This role is part of the CS AI track, which is responsible for delivering high-priority AI features aimed at improving agent efficiency and reducing human-handled tickets. As an individual contributor, you will play a key role in driving strategy, aligning stakeholders, and ensuring technical excellence—without direct people management responsibilities. Key Job Responsibilities and Duties: Develop production-grade machine learning code, from models to features and pipelines, allowing for scalability, realtime, monitoring and retraining. Build readable and reusable code, choosing the right technologies and coding methodologies applying knowledge of business area tools and product needs. Monitor product health, performance and business impact and act accordingly when requirements are not met and also identify underlying issues and opportunities across related domains and situations through application of structured thinking and logic. Solve issues by applying methods and insights gained from a variety of disciplines, navigating a variety of environments. Make things happen by maintaining motivation and conveying a sense of urgency, focusing on outcomes and accomplishments and continuously evolving their craft, keeping up to date with the latest technologies. Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, interviewing, onboarding and mentoring colleagues and clearly communicating with stakeholders at all levels when appropriate. Responsible for technical implementation and maintenance of data processing services and storage systems in line with the Data Governance Framework while collaborating with central teams to improve, scale and extend machine learning tooling and infrastructure. This role may require to be on an on-call rotation Qualifications & Skills: Strong knowledge in areas like e.g. Recommender Systems, Deep Learning, Information Retrieval, Computer Vision, Speech Recognition, Causal Inference, scaling ML models, etc. 4+ years of relevant work experience (or equivalent), involved with the application of Machine Learning to business problems, preferably in a commercial environment. Graduate in Computer Science, Artificial Intelligence, Software Engineering, or related fields with knowledge of version control systems, multiple machine learning facets, such as working with large data sets, experimentation, scalability and optimization. Experience with data-driven product development: analytics, A/B testing, etc. Strong working experience in one or more general purpose programming languages, including but not limited to: Java, Python or Perl. Excellent English communication skills, both written and verbal. 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 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 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.