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Responsibilities:
- Architect cloud infrastructure and AI/ML solutions using Kubernetes, Kubeflow, OpenStack, and public cloud platforms.
- Work across the Linux technology stack including networking, storage, virtualization, containers, and applications.
- Deliver technical presentations, demonstrations, and training sessions for customers.
Requirements:
- Bachelor's degree in a technical discipline or equivalent experience.
- Experience in data engineering, MLOps, analytics, or big data solutions.
- Hands-on knowledge of Linux, Kubernetes, and cloud platforms.
Benefits:
- Distributed work environment with twice-yearly in-person team sprints.
- Personal learning and development budget of USD 2,000 per year.
- 40 days of annual leave including public holidays and company-wide holiday periods.
Partner Company
The partner company helps organizations adopt modern AI and machine learning technologies across public and private cloud environments. They operate with a global Field Engineering team and a distributed work environment.