ML & Cloud Infra Engineer
- Create and maintain ML and cloud infra for startup AI company.
- Design and Deploy Infrastructure: Develop and maintain scalable, high-performance cloud-based infrastructure for ML workloads and serving ML APIs or client endpoints.
- Cloud Platforms: Deploy, manage, and optimize cloud-based infrastructure (AWS, Azure, GCP). Setup ML nodes for local development and distributed training workloads, maintain compatibility between the two.
- System Management: Install, configure, and monitor servers.
- Storage management: Optimize various types of shared / local storage maintaining big data for ML workloads.
- Containerization and Orchestration: Manage and scale containerized applications using Docker, Kubernetes, Terraform, etc.
- Collaboration: Work closely with the rest of the technical team to ensure smooth orchestration of the ML and production workloads.
- Incident Response: Respond to cloud / production incidents, perform analysis, and implement solutions to prevent recurrence.
- 3 years professional experience in a cloud-related role, preferred ML-related.
- Proficiency in writing scripts (Bash, PowerShell, Python, ...) to automate tasks.
- Proficiency in cloud platforms (e.g., AWS, GCP, Azure).
- Proficiency in containerization (e.g., Docker, Kubernetes).
- Proficiency in orchestrating a cloud.
- Familiarity with Python (Jupyter) and ML frameworks (PyTorch).
- Familiarity with cloud monitoring tools (e.g., Prometheus, Grafana).
- Familiarity with cloud-based database systems (Amazon RDS, Aurora, Redshift, Google Cloud SQL, Spanner, ...) and data-visualisation tools (Amazon QuickSight, Apache Superset).
- Familiarity with CI/CD tools (e.g., CircleCI).
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