MLOps Field Engineer

📋 Description Architect cloud infrastructure and AI/ML solutions using technologies such as Kubernetes, Kubeflow Work across the Linux technology stack, including networking, storage, infrastructure Design and deliver solutions for both on-premises environments and public clouds such as AWS Gather customer business and technical requirements and recommend appropriate open-source Deploy, test, validate, and hand over technical solutions to support or managed services teams Deliver technical presentations, demonstrations, architecture discussions, and training sessions 🎯 Requirements Bachelor’s degree in a technical discipline or a compelling alternative professional background. Experience in data engineering, MLOps, analytics, or deployment of big data solutions. Practical experience with a programming language such as Python, R, or Rust, with intermediate Hands-on knowledge of Linux, virtualization, containers, networking, and cloud computing concepts. Experience with Kubernetes and familiarity with cloud platforms such as AWS, Azure, or Google Cloud. Understanding of large-scale enterprise open-source technologies, private clouds, machine learning 🎁 Benefits Distributed work environment with twice-yearly in-person team sprints. Personal learning and development budget of USD 2,000 per year. Annual compensation review based on location, experience, and performance. Performance-driven annual bonus or commission. Recognition rewards. 40 days of annual leave per year, including public holidays and company-wide holiday periods.