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Mid-tier employer, Bangalore location, popular mid-level ML role with broad AI requirements increases applicant competition.
Advanced ML/AI and MLOps skills transfer across industries, though travel-specific GDS domain knowledge is preferred.
Explicit minimum experience and extensive mandatory ML, MLOps, GCP, and production engineering requirements enforce strict shortlisting.
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Architect and deploy complex AI and mathematical algorithm-based software solutions impacting Sabre's travel retailing, network planning, and departure control platforms.
Drive research and innovation focused on AI-driven automation, personalization, and real-time optimization within the travel domain.
Define and implement strategic MLOps policies, ensuring production-quality, low-latency AI systems aligned with business objectives.
Minimum 4 years of experience in Data Science, AI Engineering, or Operations Research.
Advanced degree (Masters or PhD preferred) in Mathematics, Machine Learning, Statistics, Computer Science, or Physics with strong research background.
Expertise with Python, Golang, or C++ for high-performance, latency-sensitive programming.
Proficiency in advanced ML/AI methods including Deep Learning, Reinforcement Learning, NLP and familiarity with GCP (Vertex AI, BigQuery), MLOps tools, containerization (Docker, Kubernetes).
Experienced in moving complex ML models from research to global production in Agile environments within high-volume, real-time travel or related domains.
Strategic thinker comfortable driving cross-functional projects, influencing technical and business roadmaps for travel technology and AI innovation.
Familiar with travel industry data ecosystems (GDS, OTA) and applying AI/ML to optimize workflows, automate operations, and integrate emerging AI technologies (e.g., Generative AI, LLMs).