ML Ops Engineer

Build and operate scalable AI/ML platforms, CI/CD pipelines and cloud infrastructure for ML and LLM workloads, with a focus on automation, security, observability and model lifecycle management for our client.

Key Responsibilities

• Design and manage CI/CD pipelines for ML/LLM workloads using Jenkins, GitHub Actions and Kubeflow.
• Build reusable deployment templates, workflows and platform components.
• Automate infrastructure using Terraform, Helm and Kubernetes.
• Deploy ML/LLM applications on Kubernetes and EKS/AKS/GKE.
• Implement monitoring and observability using ELK, Prometheus and Grafana.
• Ensure security, compliance and cost governance across cloud environments.
• Collaborate with Data Scientists, ML Engineers and DevOps teams.
• Mentor engineers and continuously improve platform reliability and scalability.

Technical Skills

• 8+ years total experience with 5+ years in MLOps/LLMOps or related areas.
• Strong CI/CD expertise: Jenkins, GitHub Actions.
• Python, Shell, Docker/Dockerfiles and Terraform.
• Kubernetes and managed Kubernetes services.
• Terraform, Helm and Infrastructure as Code.
• Kubeflow for ML workflow orchestration.
• ELK Stack, Prometheus and Grafana.
• Strong AWS and Azure experience.

Understanding of ML/LLM deployment and model lifecycle management