Sabre
Website:
sabre.com
Company:
https://www.linkedin.com/company/sabre-corporation
Seniority: Not Applicable
Industries: Technology, Information and Internet
Job details:
Sabre is seeking a talented Lead Data Science Engineer to support Research Team.
Sabre Labs Research team delivers as the innovation engines intelligent core of Sabre’s travel marketplace. We are a specialized group of researchers, mathematicians, and AI engineers dedicated to solving the most complex challenges across the global travel domain. Our mission spans Airline Pricing, Agency Automation, Network Planning, Airline Operations, and Departure Control Systems (DCS). We build high-performance systems that streamline travel agency workflows, optimize airline networks, and enhance the productivity of travel consultants worldwide. By blending classical mathematical optimization with cutting-edge Generative AI and robust MLOps, we ensure our models power the next generation of travel distribution—from initial search and booking to post-trip service, agency efficiency, and seamless airport operations.
At Sabre, we’re passionate about building software that solves problems. In this role, you will plan, design, develop, and test software systems or applications for software enhancements and new products including cloud-based tools.
Role And Responsibilities
- Architects, codes, and deploys complex software solutions that integrate advanced mathematical algorithms and machine learning models into Sabre’s core retailing, Network Planning, Agency Automation, and Departure Control platforms.
- Drives Research & Innovation by identifying, prototyping, and scaling new ideas within the travel domain, such as AI-driven automation for Travel Management Companies (TMCs) and personalized, real-time itinerary optimization.
- Designs end-to-end AI systems, specifically focusing on the integration of Large Language Models (LLMs) for automated agency support, customer intent recognition, and conversational commerce.
- Solves high-impact organizational challenges, such as optimizing Global Distribution System (GDS) workflows and migrating legacy automation logic into modern, GCP-based AI architectures.
- Establishes strategic AI lifecycle policies, defining rigorous standards for MLOps to ensure high-fidelity model performance across the volatile data landscapes of the travel industry.
- Promotes engineering excellence by utilizing best practices in Python and C++, ensuring research-grade prototypes are refactored into production-quality, low-latency systems.
- Collaborates with cross-functional leadership, including architects and product managers, to align technical roadmaps with business goals like NDC adoption, total travel cost optimization, and operational efficiency.
- Influences stakeholder decision-making, advocating for the adoption of disruptive technologies—including Agentic AI—within mission-critical, high-availability travel environments.
- Mentors and develops junior data scientists and engineers, fostering a culture of rigorous experimentation, academic-level research, and high-performance engineering.
Qualifications And Education Requirements
- Minimum 7 years of related experience in Data Science, AI Engineering, or Operations Research.
- Advanced Optimization Modeling skills, including Linear Programming (LP), Mixed-Integer Programming (MIP), and experience with solvers like Gurobi or CPLEX.
- Advanced Degree (PhD preferred) in Mathematics, Statistics, Computer Science, or Physics with a strong research background and a proven track record of innovation.
- Proven experience in Agile Software Development, with a demonstrated ability to move complex models from the research phase to global production.
- Expertise in advanced ML/AI solutioning, including Deep Learning, Reinforcement Learning, and Natural Language Processing (NLP).
- High-performance programming skills, with mastery of Python and C++ for computationally intensive and latency-sensitive tasks.
- Deep knowledge of the Modern AI Tech Stack, including GCP (Vertex AI, BigQuery ML), MLOps tools, and containerization (Docker, Kubernetes).
- Proficiency in Generative AI frameworks, such as LangChain or LlamaIndex, and experience with RAG-based systems for workflow automation.
- Self-motivated leadership, capable of driving complex, cross-functional projects to completion with minimal direction.
Desirable (Optional) Qualifications
- Experience in travel industry
- Domain knowledge in Airline Operations, Departure Control Systems (DCS), network planning, or route profitability.
- Superior analytical skills, particularly in processing high-volume, real-time data from GDS, OTA, and airline sources.
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