
DevOps & MLOps Engineer
2 weeks ago
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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