ML Platform Engineer

📋 Description

• Design, build, and improve platform systems for ML training, deployment, and serving.
• Build scalable infra and tools to improve ML workload reliability, efficiency, and cost.
• Develop automation workflows and tools to reduce complexity for researchers and engineers.
• Architect and maintain systems for deployment, monitoring, and operation across environments.
• Improve scheduling, monitoring, debugging, and resource management for GPU and cloud infra.
• Improve observability, automation, reliability, and developer usability.

🎯 Requirements

• Strong experience building/operating production systems with reliability and scale.
• Systems mindset to reason about bottlenecks, failures, interfaces, and resources.
• Hands-on cloud infra, Linux, and infrastructure automation experience.
• Experience operating distributed systems in production, incl. Kubernetes.
• Strong Python or backend-language programming skills.
• Experience building internal platforms and developer tooling.

🎁 Benefits

• Fully remote work environment with flexibility across Europe.
• Opportunity to work on advanced AI infrastructure supporting large-scale enterprise applications.
• High ownership role with significant influence over platform architecture and technical direction.
• Collaborative environment with close interaction between engineering, research, and product teams.
• Opportunity to solve complex challenges involving machine learning systems, automation, and distributed infrastructure.
• Professional growth opportunities within a fast-moving AI-focused organization.