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# Machine Learning Scientist I - GenAI Applications

- **Company:** Booking.com
- **Location:** Amsterdam, Netherlands (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Data Analysis, Big Data, Data Visualization, Python (Programming Language), Machine Learning, Natural Language Processing, Systems Development Life Cycle, Software Engineering, SQL Databases, Chatbots, Large Language Models, Apache Spark, Information Technology, Virtual Agents
- **Published:** June 3, 2026
- **Apply:** https://www.careerjet.nl/jobad/nl9188d9ae0abb1c4f7482172c58c66fd4

## About the Role

Bachelor's or master's degree in Computer Science, Engineering, Statistics, or a related field.
Minimum of 6 years of experience as a Machine Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions to production.
Advanced knowledge and experience in GenerativeAI models at scale, Natural Language Processing and engineering aspects of developing ML.
Experience designing and executing end-to-end research and development plans and generating impact through large-scale ML & Agentic System development.
Experience on multiple ML facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
Experience collaborating cross-functionally in the development of ML products (e.g. Developers, Product Managers, UX specialists, etc.).
Strong working knowledge of Python, LangChain, SQL, and Spark or similar technologies.
Strong coding practices, including writing and reviewing production-quality, maintainable, and well-tested code, with the ability to effectively leverage modern AI coding assistants while maintaining high standards for correctness, readability, and system design.
Excellent English communication and presentation 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

## Description

The GenAI Applications team is responsible for designing and delivering agentic, ML-powered solutions for some of our most impactful products, including booking search experiences, trip planning, and customer service. The team builds AI-driven applications and conversational agents, such as chatbots and intelligent assistants that significantly enhance the end-to-end customer experience.
Role Description:
As a Senior Machine Learning Scientist, you will work closely with engineers and product to design, develop, evaluate and deploy Gen AI powered solutions for scalable, customer-facing applications. Your work will focus on applying state-of-the-art agentic capabilities and driving business impact based on rigorous evaluations and experimentation.
Key Job Responsibilities and Duties:
Design end-to-end agentic systems, delivering high-quality, performant, and efficient solutions to production
Build agentic solutions for different tasks and use cases using state-of-the-art techniques
Develop and carry out evaluation strategies, including formulating new metrics and building evaluation judges
Pioneer and promote best practices and adoption of new technology in GenAI application development
Lead and mentor other team members, providing technical guidance and timely feedback to develop the team and motivate them to achieve their goals.
Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into ML solutions.
Conduct deep data analysis to evaluate model performance, label quality, features exploration.
Work closely with ML engineers to ensure and improve the solution's latency/throughput meets product requirements and ensure deployment of your model to production.


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