Job Objective Design, implement, and operate the automation, deployment, and monitoring infrastructure required to support the SRP Data & AI platform. Establish reliable CI/CD and MLOps pipelines, automate model deployment and lifecycle management, and ensure that machine learning and geolocation algorithms can be deployed, monitored, scaled, and continuously improved in production. Main Tasks
• Design CI/CD pipelines for AI/ML and data engineering workloads.
• Automate model training, validation, deployment, and monitoring.
• Implement ML lifecycle management, experiment tracking, and model versioning.
• Deploy and manage applications using Docker and Kubernetes.
• Implement Infrastructure as Code using Terraform and Ansible.
• Develop automated deployment workflows for AI models and services.
• Implement model monitoring, drift detection, and performance monitoring.
• Manage scalable infrastructure for distributed data processing.
• Implement observability, logging, and alerting.




• Optimize infrastructure performance, reliability, and resource utilization.
• Implement security, access control, and secrets management. Qualifications
• Bachelor's degree in Computer Science, Software Engineering, or IT.
• 4+ years of experience in DevOps, cloud engineering, platform engineering, or MLOps.
• Strong experience with Docker and Kubernetes.
• Experience with GitLab CI, GitHub Actions, Jenkins, or Azure DevOps.
• Strong knowledge of AWS, Azure, or GCP.
• Experience with Terraform and infrastructure automation.
• Familiarity with MLflow, Kubeflow, Airflow, or equivalent tools.
• Knowledge of distributed computing and big data infrastructure.
• Experience with Prometheus, Grafana, and monitoring tools.
• Robust Linux, Python, and scripting skills.

📌 DevOps / MLOps Engineer (India)
🏢 Monty Mobile
📍 India