Currently tracking 14 active AI roles, with 252 new openings in the last 4 weeks. Primary focus: Agent · Engineering.
Booking currently has 14 active AI-related job listings. The majority of these roles, 50%, are focused on agents, with application and data roles each representing 14%. Engineering is the dominant function, with 12 roles posted. The company is hiring for roles that frequently mention model serving, agent orchestration, and inference infrastructure. In the last 30 days, Booking has posted 11 new AI roles.
Booking currently has 11 active AI-related roles in our index. The most common open titles are: Data Engineer II - Content Intelligence, Data Engineer II - GenAI, Machine Learning Engineer II - Benefits & Pricing Track, Machine Learning Manager - Recommendations & Smart Positioning, Machine Learning Scientist II - Content Intelligence. Most positions are in Engineering and Research.
Booking's active AI hiring is concentrated in: agents (36%), data (27%), application (18%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Booking is hiring AI talent in: Netherlands (6 roles), Israel (4 roles), United Kingdom (1 role).
Job postings at Booking most frequently mention: Machine Learning, Python, Market & Technology Trend Analysis, TensorFlow, Supervised Fine-Tuning (SFT).
In the past 30 days, Booking has posted 5 new AI-related roles. That is a -58% change versus the prior 30 days (12 → 5).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Scientist II - Content Intelligence Machine Learning Scientist II at Booking.com focused on the Content Intelligence team. The role involves building, training, and deploying content models (Computer Vision, NLP, Generative AI) and in-house LLMs for applications like moderation, translation, AI trip planner chatbot, and content generation. Responsibilities include exploring state-of-the-art techniques, training innovative ML models, engineering reusable frameworks, conducting data analysis, and collaborating with ML engineers and product teams for production deployment. | Post-trainAgent | 8 |