ML Platform Engineer

📋 Description

• Design and build platform systems for ML training, eval, deployment, and serving.
• Build scalable infra and tooling to boost reliability, efficiency, and cost.
• Develop automation workflows and internal tools to reduce ops complexity.
• Architect systems enabling efficient model deployment, monitoring, and ops.
• Improve workload scheduling, monitoring, and resource mgmt for GPU/cloud infra.
• Drive observability, automation, reliability, and developer experience across the platform.

🎯 Requirements

• Strong experience building/operating production systems with reliability, scalability, and performance.
• Cloud infra, Linux environments, and infrastructure automation.
• Production distributed systems experience, incl. Kubernetes.
• Strong programming skills in Python or similar backend languages.
• Understanding of ML infrastructure, model serving, or data-heavy workloads.
• Experience with GPU-based systems and large-scale computing resources.

🎁 Benefits

• Fully remote work environment with flexibility across Europe.
• Opportunity to work on advanced AI infrastructure for enterprise apps.
• High ownership role with influence over platform architecture and direction.
• Collaborative environment with close engineering, research, and product collaboration.
• Opportunity to solve complex ML systems, automation, and distributed infra challenges.
• Professional growth opportunities within a fast-moving AI-focused organization.