Senior Machine Learning Scientist (Marketplace)

• The Agentic Modeling team is responsible for enabling mission teams across Booking
• Com to build, deploy, and continuously improve production-grade AI agents — without requiring deep AI expertise
• We provide a modular, configuration-driven platform where teams compose reusable building blocks — tools, memory, context management, agent strategies, and system prompts — into custom agents tailored to their domains
• Our SDK and tooling support the full agent lifecycle: building, evaluating, optimizing, publishing, and iterating on agents that power the Connected Trip experience
• As a Senior Machine Learning Scientist, you will research, design, and develop the core AI capabilities that power our agentic platform — focusing on agent strategies, reasoning architectures, context management, memory systems, and multi-agent patterns
• You will work at the intersection of LLM research and production systems, translating state-of-the-art techniques into reusable, scalable capabilities that teams across Booking.Com can leverage through configuration
• Research and develop advanced agent strategies - iterative planning, self-correction, multi-step reasoning, and conditional execution paths
• Design and build context management and memory systems (session-level and long-term) that enable personalized, improving agent experiences
• Research and implement multi-agent patterns - enabling specialized agents to collaborate, share context, and delegate sub-tasks
• Help build systematic experimentation and optimization - model selection, strategy comparison, prompt engineering, and architecture decisions backed by quantitative analysis
• Build reusable ML components that encode production best practices and are available to all teams through configuration
• Collaborate closely with ML engineers to ensure research translates into production-grade capabilities with appropriate latency and reliability
• Collaborate with cross-functional teams (product managers, mission teams, platform engineers) to translate business requirements into agent capabilities

Benefits

• Health insurance
• Free access to Headspace for you and your loved ones
• Global Employee Assistance Program
• Meditation and Breastfeeding rooms at the office
• Booking Cares - 2 days per year to volunteer and learn
• Life insurance
• Disability insurance
• Pension plan
• Annual paid time off
• Parental leave - 22 weeks
• Grandparent leave - 10 days
• Care leave - 10 days
• Bereavement leave - up to 4 weeks
• Anniversary leave
• Working from Home Furniture and Ergonomic Support
• Working from Abroad - up to 20 days per year
• Discounts & Wallet credits to spend on our products
• Upgrade to Booking.com Genius Level 3
• Friends & Family Booking.com discount vouchers
• Free access to online learning platforms
• Development and mentorship programs to support career growth
• Access to trainings and workshops
• Team development opportunities
• Local discount programs
• Game rooms in offices
• On-site meals, coffee and snacks including vegan options- Strong working knowledge of Python and ML/AI frameworks. Experience with LLM APIs and retrieval systems
• Excellent English communication skills, both written and verbal
• Leading by example, developing your team and motivating them to achieve their goals. Providing timely feedback and managing key performance indicators
• Experience designing and building production agentic or conversational AI systems at scale
• Experience designing and executing end-to-end R&D plans. Preferably evidenced by peer-reviewed publications, patents, or open-source contributions
• Masters degree, PhD or equivalent experience in a quantitative field (e.g., Computer Science, Artificial Intelligence, Mathematics, Physics, etc.)
• Experience collaborating cross-functionally in the development of ML-powered products
• Successfully driving technical and people-related initiatives while communicating with stakeholders at all levels
• Advanced knowledge and experience in NLP, LLM-based systems, and agentic AI architectures - including tool use, reasoning, retrieval-augmented generation, and agent planning
• Experience with LLM evaluation and optimization - designing metrics and systematically improving model-based systems
• Relevant work or academic experience (MSc + 6 years, or PhD + 4 years), applying Machine Learning to business problems