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You will focus on execution across model lifecycle activities, production reliability, and the infrastructure that supports both platform environments and delivered products.\nAirline Platform is a cross domain Data and AI platform that enables teams to deliver reliable, secure, and scalable data and AI and ML products. It uses Google Cloud Platform, BigQuery, Docker, Kubernetes, Terraform, CI and CD pipelines, and GenAI tooling to support the full product lifecycle.\nBuild, deploy, and operate ML and GenAI models and services end to end following MLOps practices\nDevelop and maintain data and AI products within the platform domains\nEnable and harden the shared Data and AI platform including environment and product infrastructure\nOrchestrate and maintain reliable data and model pipelines ensuring quality and availability for downstream consumers\nApply Infrastructure as Code with Terraform and CI and CD standards for data and AI workloads\nInstrument observability and monitoring for models and services and act on performance and cost\nParticipate in design and code reviews\nDocument the processes built\nAround 3 years of proven experience as an MLE, ML Ops, AI engineer, or similar role\nStrong Python with experience deploying and serving models in production\nHands on end to end MLOps including 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