Back
Senior, niche ML/AI role at a known travel-tech firm in Bangalore yields medium competition.
Core ML and MLOps skills are transferable, but travel-specific GDS and latency requirements raise domain sensitivity to medium.
Explicit 10+ years, PhD preferred, and strict ML, MLOps, GCP and C++ requirements increase shortlisting strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Designs, develops, and deploys advanced AI and mathematical algorithm-based software solutions for Sabre's travel retailing, network planning, agency automation, and departure control platforms.
Leads research and innovation initiatives including integrating Large Language Models (LLMs) for automated agency support and real-time itinerary optimization within high-impact travel systems.
Defines strategic AI lifecycle policies and MLOps standards, mentors junior team members, and collaborates with leadership to align AI technology roadmaps with travel business goals.
Minimum 10 years of experience in Data Science, AI Engineering, or Operations Research.
Advanced degree (PhD preferred) in Mathematics, Statistics, Computer Science, or Physics with strong research and innovation track record.
Proficiency in Python and C++ for high-performance, latency-sensitive programming.
Expertise in ML/AI solutioning including Deep Learning, Reinforcement Learning, NLP, modern AI tech stack (GCP, MLOps, containerization), and Generative AI frameworks (LangChain, LlamaIndex).
Experienced in transitioning complex AI/ML models from research to production in global, high-availability environments.
Familiar with travel domain data sources (GDS, OTA, airline) and modern AI architectures including cloud-native and MLOps best practices.
Capable of leading cross-functional AI innovation projects, influencing stakeholders, and integrating advanced optimization and generative AI technologies effectively.