Platform, Cloud & MLOps Engineer

Platform, Cloud & MLOps Engineer

Location: Gurugram

Experience: 5+ years

What we need:

We need an engineer who can build, manage, and automate cloud infrastructure and Kubernetes platforms for applications, data, and AI/ML workloads.

Key Skills Required:

• Cloud & DevOps: Hands-on experience with cloud platforms, Linux, Docker/containers, and Kubernetes.
• Infrastructure Automation: Experience with Terraform, Ansible, and Infrastructure as Code (IaC).
• CI/CD & GitOps: Ability to automate application deployment and infrastructure updates.
• MLOps: Experience managing ML pipelines, model training, model registries, deployment, and monitoring.
• GPU & AI Model Deployment: Knowledge of GPU infrastructure, NVIDIA tools, model serving, and autoscaling.
• Monitoring & Security: Experience with observability, networking, storage, access controls, backups, and disaster recovery.
• Scripting: Python or Go.

Preferred:

• Experience working in large enterprise or public-sector environments.
• Relevant cloud, Kubernetes, DevOps, or MLOps certifications.
• Familiarity with AI coding assistants such as GitHub Copilot or Microsoft Copilot.

What kind of candidate should we target?

Look for a DevOps Engineer, Platform Engineer, Cloud Engineer, or MLOps Engineer with strong Kubernetes and infrastructure automation experience, plus practical exposure to deploying and managing machine-learning models.

Important: We need more than a traditional DevOps engineer. The candidate should have actual MLOps/model deployment experience, ideally including GPU-based workloads and NVIDIA technologies.