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.
Currently tracking 14 active AI roles, with 215 new openings in the last 4 weeks. Primary focus: Agent · Engineering.
Booking currently has 13 active AI-related roles in our index. The most common open titles are: Data Engineer II - GenAI, Data Scientist- Performance Marketing, Director of Technology - Customer Service, Machine Learning Engineer II - Benefits & Pricing Track, Machine Learning Manager - Recommendations & Smart Positioning. Most positions are in Engineering and Product.
Booking's active AI hiring is concentrated in: application (31%), agents (31%), serving infrastructure (15%). 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 (3 roles).
Job postings at Booking most frequently reference: model serving, recommender systems, agent orchestration, llm observability, search ranking.
In the past 30 days, Booking has posted 11 new AI-related roles. That is a +120% change versus the prior 30 days (5 → 11).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Scientist I - Performance Marketing Machine Learning Scientist role focused on optimizing large-scale ML models for online bidding in performance marketing. The role involves developing advanced ML and optimization techniques for bidding algorithms, modeling user intent and marketplaces, and optimizing bidding strategies to maximize advertising budget efficiency. It also includes designing and implementing scalable evaluation pipelines, synthetic data generation, and benchmarking for model quality. The position requires a strong understanding of large-scale optimization, auction theory, and applying ML to industrial setups, with a focus on end-to-end research-to-production cycles and A/B testing. | AgentEval Gate | 7 |