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Senior Machine Learning Scientist

Booking.com · Amsterdam Centrum, NH, NL

Amsterdam Centrum, NH, NL · On-siteFull-TimePosted Jun 18, 2026

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Job description

Role Description:

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 make. The journeys you take. The sights you see. And the food you sample. Through our products, partners and people, we can empower everyone to experience the world.

We’re looking for a Senior Machine Learning Scientist I to join our Travel LLMs and Agentic team in Amsterdam.

About the team:

The team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search.

The team you are applying to is spearheading a research effort to develop leading LLMs, specifically designed for the travel domain and advanced agentic capabilities.

This pioneering initiative combines cutting-edge AI research with practical applications, focusing on creating tailored solutions that redefine how travelers plan, book, and experience their journeys.

Role Description:

As a Machine Learning Scientist, your work will focus on building, training, and deploying cutting-edge Generative AI models. This includes developing foundation models trained on Booking.com’s extensive textual data and creating fine-tuned models designed to tackle complex travel-related tasks. Your leadership will play a pivotal role in advancing the application of AI to transform the travel experience for millions of customers.

Key Job Responsibilities and Duties:

  • Explore and apply state-of-the-art techniques in multimodal machine learning.
  • Train innovative ML models (NLP, CV, LLM-finetuning…), build algorithms, and engineering approaches to drive business impact..
  • Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
  • Conduct data analysis with detailed metrics to evaluate model’s performance, labels quality, features exploration.
  • Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
  • Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Role Qualifications and Requirements:

  • Advanced knowledge and experience in Computer Vision and Natural Language Processing, engineering aspects of developing ML and Generative AI models at scale.
  • Experience designing and executing end-to-end research and development plans and generating impact through large-scale machine learning model development. Preferably evidenced by peer-reviewed publication, patents, open sourced code or the like.
  • Relevant work or academic experience (MSc + 6 years of working experience, or PhD + 4 years of working experience), involved in the application of Machine Learning to business problems.
  • Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).
  • Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
  • Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).
  • Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.
  • Excellent English communication skills, both written and verbal.
  • Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels
  • Leading

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