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.
- Robust 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.
- Strong Linux, Python, and scripting skills.

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