- Proven experience in IT infrastructure operations and management.
- Hands-on experience with AI/ML Platform Concepts and tools (e.g.,
MLflow, Kubeflow).
- Proficiency in CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions).
Solid understanding and practical experience with Cloud Infrastructure
Management (Azure – preferred, AWS or GCP).
- Expertise in Containerization technologies, particularly Docker and Kubernetes for AI workloads.
- Experience with GPU hardware management and optimization for AI/ML tasks.
- Demonstrated ability in Infrastructure as Code (IaC) using tools like Terraform or Ansible.
- Strong Linux Administration skills.
- Experience with Monitoring and Alerting Tools (e.g., Prometheus, Grafana).
- Fundamental understanding of Networking concepts relevant to distributed systems.
- Proficiency in scripting languages such as Python and Bash for automation.
- Knowledge of Security Best Practices for Infrastructure.
- Excellent Troubleshooting and Problem-Solving abilities.