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Senior specialized ML role at a known travel-tech firm in a metro reduces broad applicant density to medium.
Requires deep ML/optimization, travel GDS data understanding, and low-latency engineering, making cross-industry fit low-high sensitive.
Explicit 10+ years, advanced degree preference, and specific ML, MLOps, and low-latency tech stack imply high strictness.
Architect, implement, and deploy complex AI and mathematical algorithms into Sabre’s core travel retailing and operations platforms.
Design and scale innovative AI systems including Large Language Model integration for automated agency support and real-time itinerary optimization.
Lead strategic AI lifecycle and MLOps policies to maintain high model fidelity across dynamic travel data streams.
Minimum 10 years experience in Data Science, AI Engineering, or Operations Research.
Advanced degree required; PhD preferred in Mathematics, Statistics, Computer Science, or Physics with strong research background.
Proven expertise in Python and C++ programming for performance-critical AI/ML applications.
Experience with cloud AI technologies (GCP Vertex AI, BigQuery ML), MLOps, containerization (Docker, Kubernetes), and advanced ML techniques (Deep Learning, Reinforcement Learning, NLP).
Experienced leader able to drive cross-functional projects from research through global production deployment in AI and travel tech environments.
Deep technical knowledge of advanced AI, optimization methods, and generative AI frameworks applied to high-volume, real-time travel data.
Strong domain orientation toward travel industry challenges like Agency Automation, Network Planning, and Global Distribution System workflows.