DevOps & MLOps Engineer

2 weeks ago

Islamabad, Islamabad, Pakistan FORBMAX Full time 900,000 - 1,200,000 per year

DevOps & MLOps Engineer

Experience Required:
2-3 years

Employment Type:
Full-time

Position Overview

We are seeking a DevOps & MLOps Engineer to manage our on-premise Kubernetes infrastructure and machine learning operations. This role involves maintaining system reliability, automating deployment processes, and supporting ML model deployment.

Key Responsibilities

Infrastructure Management

  • Administer on-premise Kubernetes clusters
  • Maintain system availability and performance
  • Implement monitoring and troubleshooting procedures

MLOps Operations

  • Deploy and manage Kubeflow
  • Configure and maintain Triton Inference Servers
  • Support machine learning model deployment processes

Automation and CI/CD

  • Develop GitHub Actions & Jenkins workflows
  • Automate deployment and testing processes
  • Maintain infrastructure as code practices

Collaboration

  • Work with development and AI teams
  • Document processes and procedures
  • Participate in technical planning and reviews

Required Qualifications

Experience

  • 2-3 years in DevOps or MLOps roles
  • Hands-on experience with Kubernetes cluster administration
  • Working knowledge of Kubeflow for ML and Models management
  • Experience with GitHub Actions and Jenkins for automation
  • Familiarity with Triton Inference Server deployment
  • Understanding of cloud-native technologies

Core Technologies

  • Container Orchestration:
    Kubernetes, Docker, Helm
  • CI/CD:
    GitHub Actions, GitLab CI, Jenkins
  • Infrastructure as Code:
    Terraform, Ansible
  • Monitoring & Observability:
    Prometheus, Grafana
  • Operating Systems:
    Linux (Ubuntu, CentOS, RHEL)
  • Scripting:
    Python, Bash, PowerShell, YAML
  • Version Control:
    Git, GitHub, GitLab

MLOps Technologies

  • ML Platforms:
    Kubeflow, MLflow
  • Model Serving:
    Triton Inference Server, TorchServe
  • ML Frameworks:
    TensorFlow, PyTorch, scikit-learn
  • Data Processing:
    Apache Spark, Kafka, Pandas

Cloud & Infrastructure

  • Cloud Platforms:
    AWS, Azure, GCP (knowledge helpful)
  • Databases:
    PostgreSQL, MySQL, MongoDB, Redis
  • Storage:
    MinIO, Ceph, NFS, distributed storage systems
  • Networking:
    Load balancers, Ingress controllers, Service mesh (Istio)
  • Security:
    RBAC, SSL/TLS, Vault, container security scanning

Preferred Qualifications

  • Experience with GPU workload management
  • Knowledge of serverless technologies
  • Familiarity with service mesh architectures
  • Experience with backup and disaster recovery solutions
  • Previous work in regulated or enterprise environments

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