MLOps Field Engineer

📋 Description

• Design and architect AI/ML, MLOps, data engineering, and cloud infrastructure solutions aligned
• Work across the Linux technology stack, including networking, storage, containers, applications
• Architect and deploy solutions using Kubernetes, Kubeflow, OpenStack, Spark, and related open
• Deliver solutions across on-premises environments and major public cloud platforms, including AWS
• Engage directly with customers to understand technical and business requirements and recommend
• Deploy, test, troubleshoot, and validate technical solutions before handing them over to support or

🎯 Requirements

• Professional experience in MLOps, data engineering, big data, cloud infrastructure, or the
• Practical experience with Linux, virtualization, containers, networking, and cloud infrastructure.
• Experience with Kubernetes and familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Working knowledge of MLOps, AI/ML infrastructure, data processing pipelines, distributed systems
• Intermediate Python programming skills, with experience in another language such as R or Rust
• Understanding of open source technologies and an interest in enterprise applications of private

🎁 Benefits

• Geographically adjusted compensation based on location, experience, and performance.
• Performance-driven annual bonus or commission in addition to base compensation.
• Fully distributed work environment with twice-yearly in-person team sprints.
• Personal learning and development budget of USD 2,000 per year.
• Annual compensation review.
• Recognition rewards.