Senior Machine Learning Scientist

Booking.com; Amsterdam; On-site; EUR 120,000 - 170,000; Full time

Benefits offered by this job

Health insurance

Hybrid work

Stock options

Wellbeing programs

Learning opportunities

Job summary

Booking.com in Amsterdam is seeking a Senior Machine Learning Scientist I to join the Travel LLMs and Agentic team. You will build and deploy cutting-edge Generative AI models to power travel chatbots, search, and recommendations.

You’ll lead end-to-end ML projects, collaborate with product managers, data scientists, and engineers, and push the boundaries of NLP and CV at scale while ensuring production quality and responsible AI practices.

Qualifications

• Advanced knowledge of computer vision and NLP; scalable ML models.
• Experience designing end-to-end R&D plans with measurable impact.
• MSc + 6 years or PhD + 4 years applying ML to business problems.
• Masters or PhD in Computer Science, AI, or related quantitative field.

Responsibilities

• Build, train, and deploy cutting-edge Generative AI models (NLP/LLM)
• Develop foundation models and fine-tuned variants for travel domain tasks.
• Collaborate with ML engineers, PMs, and data scientists to drive business impact.
• Ensure production readiness, latency/throughput targets, and robust evaluation metrics.

Skills

NLP

CV

Python

Java

ML at scale

English communication

Education

MSc in a quantitative field

PhD in relevant field

Tools

Kafka

Hadoop

SQL

Spark

Job 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 by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators

Benefits & Perks: Global Impact, Personal Relevance

• Headquarters located in one of the most dynamic and cosmopolitan cities in Europe: Amsterdam.
• Contribute to a high scale, sophisticated, world-class product and see the real time impact of your work on millions of travelers worldwide.
• Be part of a truly international fast paced environment and performance driven culture.
• Performance-based company that offers career advancement, and lucrative compensation, including bonuses and stock potential.
• Discount on Booking.com accommodations with the “Booking Deal” including other perks and benefits.
• Company-sponsored family and social activities to help our employees become integrated with each other and the company's culture.
• Diverse and creative colleagues from every corner of the world.
• Health, life, and disability insurance*
• 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 for yourself, friends, and family, including automatic Genius Level 3 status and quarterly Booking.com wallet credit.
• Free access to online learning platforms, development and mentorship programs, and a complimentary Headspace membership

#ThinkInclusion: Wellbeing & Inclusion at Booking.com:

Inclusion, Diversity, Belonging, Wellbeing and Volunteering (IDBWV) 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 create a unique 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 will ensure that individuals with disabilities are provided reasonable adjustment to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

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.