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

Work arrangement
No