Machine Learning Engineer

Role Description

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 Financial Planning & Analysis team acts as the analytical engine of the finance organization, providing critical insights and recommendations that shape a company’s financial health and strategic direction. As a Machine Learning Engineer, you will be part of the “Forecast of the Future” program which will be responsible for implementing ML based statistical forecasting models at the core of our financial forecasting & budgeting process, with the aim to make our forecasts more agile, accurate, scenario-based and connected (driver-based and multi-vertical).

Role Description:

We are seeking an experienced Machine Learning Engineer to join our Financial Planning & Analysis (FP&A) team, focusing on advanced forecasting initiatives. In this role, you will design, develop, deploy, and maintain machine learning solutions—primarily in the areas of time series forecasting and regression modeling—to drive data-driven financial planning and decision-making. You will play a key role in operationalizing ML models at scale using MLOps best practices, with a strong emphasis on AWS SageMaker, Airflow, Anaplan (PlanIQ) and cloud-based ML infrastructure.

Key Job Responsibilities and Duties:

• Work in a multi-disciplined, highly skilled team where you will be developing scalable production-grade data and ML pipelines across the entire ML cycle while working closely with the teams’ applied machine learning scientists
• Develop, implement, and optimize time series forecasting and regression models for financial planning, budgeting, and scenario analysis
• Support the implementation of ML pipelines using MLOps principles, ensuring robust CI/CD, reproducibility, and model governance
• Leverage AWS SageMaker for model development, training, deployment, and lifecycle management, including use of Data Wrangler, Model Registry and Feature Store
• Develop, schedule, and orchestrate data and ML workflows using Airflow, ensuring reliable and repeatable model training, evaluation, and deployment processes
• Monitor model performance, detect model drift, and implement retraining strategies to maintain accuracy and relevance over time
• Ensure data quality, feature engineering, and preprocessing of large, complex financial datasets
• Drive a culture of quality for all ML practitioners, maintain data security, integrity and quality, and make choices over the right technologies and coding methodologies
• Continuously evolve your craft, keeping up to date with the latest technologies

Qualifications and Skills:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field
• 2+ years of relevant work experience, involved with the application of Machine Learning Engineering to business problems in a commercial environment
• Strong skills in coding and problem solving. Proficiency in at least one programming language; preferably Python and strong command of SQL is strictly required. Knowledge of Snowflake is a plus. Knowledge of PlanIQ (Anaplan) is a plus.
• Experience running Machine Learning systems in production is a must, with knowledge on how to generate predictions for ML frameworks with high throughput
• Proficiency in Airflow & AWS SageMaker for end-to-end ML workflows, including model training, deployment, and monitoring
• Familiarity with additional AWS services (e.g., Lambda, ECS, CloudWatch) and infrastructure-as-code tools is a plus
• Solid understanding of cloud platforms, containerization, and version control (e.g., Docker, Git)
• Proven experience building and deploying forecasting models (time series, regression) in a financial or business analytics context
• Demonstrable experience of multiple machine learning facets, such as working with large data sets, experimentation, scalability and optimization
• Willingness to learn and understand complex and multidisciplinary business problems and concepts related to Booking.com business operations especially in finance
• You have a ‘can do’ attitude and you act proactively and not reactively
• 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
• 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

Pre-employment screening

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.