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DevOps / MLOps Engineer

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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

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