Job Title: DevOps / MLOps Engineer

Experience: 7–9 Years 
Location: Remote 
 

Job Summary

We are seeking a skilled DevOps Engineer with hands-on MLOps experience to design, automate, and manage scalable infrastructure and CI/CD pipelines for cloud-native and machine learning workloads. The role requires strong expertise in automation, container orchestration, and continuous delivery, with a focus on reliability, performance, and scalability.
 

Key Responsibilities

• Design, build, and maintain CI/CD pipelines using Jenkins and automation tools

• Implement and manage MLOps pipelines for model training, deployment, monitoring, and retraining

• Deploy, manage, and scale containerized applications using Kubernetes

• Automate infrastructure provisioning and configuration using IaC tools

• Manage cloud infrastructure and services on Google Cloud Platform (GCP)

• Ensure high availability, security, and performance of platforms and pipelines

• Collaborate with data scientists and engineers to productionize ML models

• Monitor systems, optimize costs, and troubleshoot production issues
   

Required Skills & Experience

• Strong experience as a DevOps Engineer with exposure to MLOps practices

• Hands-on expertise with Kubernetes (deployment, scaling, networking)

• Strong experience with Jenkins for CI/CD automation

• Experience with automation and scripting tools (Terraform, Ansible, Bash, Python, etc.)

• Strong understanding of containerization (Docker) and microservices architecture

• Experience with monitoring, logging, and alerting solutions
   

Nice to Have

• Experience with ML platforms such as Kubeflow, Vertex AI, or MLflow

• Knowledge of GitOps tools (ArgoCD, Flux)

• Experience with security, IAM, and compliance in cloud environments