Role Description:
In this role, you will lead a team of Machine Learning Scientists, ML and Data Engineers dedicated to building, evolving, and scaling Booking.com's agentic AI platform. This includes developing reusable agent types (classification, entity extraction, guardrails, summarization, general-purpose), agent strategies for planning and reasoning, memory capabilities, context management, and multi-agent patterns .
As a technical manager, you should be passionate about agentic AI systems, keep up to date with recent breakthroughs in LLM agents, tool use, and reasoning, define and shape the team's ML roadmap, and not be afraid to get your hands dirty with code when needed.
You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with product managers and mission stakeholders to define and shape the roadmap. You will work independently and be responsible for making technical decisions within your team.
When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with Product Managers.
Key Job Responsibilities and Duties:
Leadership in Agentic AI Development — Build, guide, and mentor a team of ML scientists and engineers in developing agent types, strategies, SDK capabilities, and production tooling for AI agents at scale.
Platform & SDK Strategy — Define and communicate the technical vision for the agentic modeling platform, ensuring it scales across missions (Trip Planning, Search, AITP, Trip Support, Content) and enables teams to go from idea to production agent in days, not months.
Agent Strategy & Reasoning — Drive development of advanced agent planning capabilities: iterative reasoning, self-correction, multi-step logic with conditional paths, and multi-agent collaboration patterns.
Context & Memory Systems — Lead the design and implementation of smart context management and agent memory (short-term session state, long-term episodic and semantic memory) as configurable building blocks.
Evaluation & Optimization — Own the integration with evaluation frameworks and production data tooling to enable systematic agent improvement across accuracy, latency, cost, and reliability.
Developer Experience — Drive improvements to developer tooling (Claude Code integration, AI Studio), ensuring low barriers to entry and fast iteration cycles for mission teams.
Foster a culture of collaboration, innovation, and excellence within the team.
Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
Translate machine learning vision and strategy into planning and execution, and ensure timely delivery.
Monitor product health, performance and business impact and act accordingly when requirements are not met.
Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic.
Drive, coach and mentor others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
Continuously evolve your craft. Keep up to date with industry and academic standard methodologies in agentic AI, LLM tool use, and agent frameworks; introduce them to the ML community and promote their application where they can generate impact.
Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, interviewing, onboarding and mentoring colleagues.
Push for improvements, scaling and extending machine learning tooling and infrastructure, collaborating with central teams.
Qualifications & Skills:
Leadership Experience: At least 3 years of experience leading ML teams in NLP, Generative AI, or Agentic AI domains, with a proven ability to guide teams in achieving impactful results.
Agentic AI Expertise: Deep knowledge of LLM-based agent architectures — tool use, function calling, planning strategies (ReAct, chain-of-thought, iterative reasoning), memory systems, and multi-agent patterns. Experience building or leading teams that ship agent-based products at scale.
Platform & SDK Mindset: Experience building reusable ML platforms, SDKs, or frameworks consumed by multiple teams. Strong intuition for developer experience, API design, and configuration-driven architectures.
Academic and Applied Background:
MSc with 6+ years of professional experience, or PhD with 4+ years of experience, applying Machine Learning to solve business challenges.
Master's, PhD, or equivalent experience in a quantitative field (e.g., Computer Science, Engineering, Mathematics, Artificial Intelligence, Physics, etc.).
Strong advantage for candidates with research or applied experience in NLP, dialogue systems, or agentic AI.
End-to-End R&D Proficiency: Demonstrated experience in designing and executing end-to-end research and development plans, from problem definition and prototyping to production deployment and monitoring.
Proven Impact: A track record of delivering measurable business value through the development and implementation of large-scale ML systems.
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.
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 key team performance indicators.
Benefits & Perks - Global Impact, Personal Relevance:
Booking.com's Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive compensation and benefits package, as well unique-to-Booking.com benefits which include:
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 - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit
Diversity, Equity and Inclusion (DEI) at Booking.com:
Diversity, Equity & Inclusion 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 build an outstanding 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 ensure that colleagues with disabilities are provided the adjustments and tools they need to participate in the job application and interview process, to perform crucial job functions, and to receive other benefits and privileges of employment.
Application Process:
Let’s go places together: How we Hire This role does not come with relocation assistance.
Booking.com is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive.
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.
