Description

We are seeking an experienced DevOps / MLOps Engineer to support a large-scale data and AI platform initiative on Google Cloud Platform (GCP). This role is responsible for building and operating the CI/CD, infrastructure automation, and machine learning lifecycle capabilities that allow data science and engineering teams to move models and data pipelines from experimentation to production reliably, securely, and at scale. The role requires solid expertise in Azure DevOps, cloud infrastructure, containerization, automation, and ML model operations, along with the ability to deliver production-grade platforms aligned with business requirements and project timelines.
Key Responsibilities
• Design, build, and maintain CI/CD pipelines in Azure DevOps (YAML pipelines, Azure Repos, Azure Artifacts, service connections, environments, and approval gates) for data pipelines, ML models, and application services deployed to GCP.
• Provision and manage GCP infrastructure using Infrastructure as Code (Terraform) executed through Azure Pipelines, covering GKE, Cloud Run, BigQuery,



Cloud Storage, Vertex AI, Composer, and networking/IAM.
• Build and operate end-to-end MLOps workflows on Vertex AI (or equivalent), including feature stores, training pipelines, model registry, automated evaluation, and deployment to batch and online endpoints, triggered and governed through Azure DevOps.
• Containerize and orchestrate workloads with Docker and Kubernetes (GKE), including Helm charts, autoscaling, and resource optimization for training and inference jobs.
• Implement model monitoring for drift, data quality, performance degradation, and cost, with automated alerting and retraining triggers.
• Establish reproducibility and governance practices: experiment tracking (MLflow / Vertex Experiments), data and model versioning, lineage, branching strategies, and promotion gates across dev, UAT, and production environments.
• Implement observability across platforms and services us

📌 Data Engineer (Ahmedabad)
🏢 Qatar Airways
📍 Ahmedabad