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.