ML Platform Engineer

📋 Description

• Design, develop, and improve platform systems for ML training, eval, deployment, and serving.
• Build scalable infrastructure and tooling to improve reliability, efficiency, and cost.
• Develop automation workflows and agent-oriented tools to reduce operational complexity.
• Architect and maintain systems enabling model deployment, monitoring, and ops.
• Improve workload scheduling, monitoring, and resource management for GPU/cloud infra.
• Drive observability, automation, reliability, and platform usability.

🎯 Requirements

• Strong experience building/operating production systems with reliability and scalability.
• Cloud infrastructure, Linux, and infrastructure automation experience.
• Experience operating distributed systems in production, incl. Kubernetes.
• Strong programming skills in Python or similar backend languages.
• Experience building internal platforms, tooling, or infrastructure abstractions.
• Familiarity with ML infrastructure, model serving, or data-intensive workloads.

🎁 Benefits

• Fully remote work with flexibility across Europe.
• Work on advanced AI infrastructure for enterprise applications.
• High ownership role with influence over platform architecture.
• Collaborative environment with engineering, research, and product teams.
• Solve complex ML, automation, and distributed infra challenges.
• Professional growth opportunities in a fast-moving AI org.