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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer II - Performance Marketing - **Company:** Booking.com - **Location:** Amsterdam, Netherlands - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), A/B Testing, Artificial Intelligence, Amazon Web Services, Online Auctions, Big Data, BigQuery, Software Quality, Code Reuse, Computer Programming, Data Governance, Data Structures, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Data Processing, Pytorch, Snowflake, Pandas, Matplotlib, Pyspark, Scikit Learn, Information Technology, Machine Learning Operations, Code Restructuring - **Published:** May 20, 2026 - **Apply:** https://www.careerjet.nl/jobad/nl266976cfb05cef63dc7148f7d6a70849 ## About the Role Bachelor's or master's degree in Computer Science, Engineering, Statistics, or a related field. Minimum of 4 years of experience as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions. Strong programming skills in languages such as Python and Java. Experience with cloud frameworks like GCP/AWS for training, evaluation and serving ML models using TensorFlow, PyTorch, or scikit-learn. Experience with big data processing frameworks such, BigQuery, PySpark, Snowflake or similar frameworks. Deep understanding of machine learning algorithms, statistical models, and data structures. Experience in deploying and inference for large-scale machine learning models - an advantage. Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage. Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage. Experience of working on products that impact a large customer base - an advantage. Excellent communication in English; written and spoken. ## Description About the team: The Performance Marketing team builds and optimizes large-scale ML systems for online bidding across all major search providers, owning one of the industry's largest online advertising optimization platforms to keep Booking.com competitive. We run end-to-end research-to-production cycles-from POC models to production A/B tests-driving measurable impact by innovating in online auctions at scale. Role Description: As a Machine Learning Engineer at Booking.com, you will play a key role in shaping how millions of travelers experience our products. You'll work closely with ML scientists, software engineers, and product managers to turn business challenges into scalable, reliable ML solutions. Beyond delivery, you'll also contribute to applied research and reusable frameworks, ensuring Booking.com remains at the forefront of AI innovation. Key Job Responsibilities and Duties Develop production-grade ML systems, from models to features and pipelines, accounting for reliability, scalability, real-time requirements, monitoring and retraining. Build readable and reusable code, applying code quality best practices and using standard libraries. Choose the right technology or coding methodology as well as refactor and simplify code when necessary. Take full ownership of your services end to end by actively monitoring the systems health, performance and business impact. Be responsible for business related data governance processes, the technical implementation and maintenance of data processing services and storage systems, and the implementation and maintenance of ML governance processes. Evaluate possible architecture solutions taking into account the business and technology requirements. Set the relevant service level objectives SLOs and act accordingly when they are not met. 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. Contribute to the internal ML/AI community by sharing your knowledge and participating in our internal ML programs. Coach others through evidence and clear communication, explaining advanced technical concepts in simpler terms. Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of disciplines and related fields. Achieve mutually agreeable solutions by staying adaptable, communicating ideas in clear coherent language and practising active listening ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Vectorize all the things! 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