ML Platform Engineer

📋 Description

• Design, develop, and improve platform systems for ML model training and deployment.
• Build scalable infra and tooling to improve reliability, efficiency, and cost of ML workloads.
• Develop automation workflows and internal tools for researchers and engineers.
• Architect and maintain deployment, monitoring, and operation systems across research and product.
• Improve scheduling, monitoring, and resource management for GPU and cloud infra.
• Drive observability and developer experience improvements across the platform.

🎯 Requirements

• Experience building or operating production systems focused on reliability and scalability.
• Systems mindset to reason about bottlenecks, failures, interfaces, and resources.
• Hands-on cloud infra, Linux, and infrastructure automation.
• Experience operating distributed systems in production, including Kubernetes.
• Strong Python or backend programming skills.
• Understanding of ML infrastructure, model serving, or data workloads.

🎁 Benefits

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