ML Platform Engineer

📋 Description

• Design and improve platform systems for ML model training, deployment, and serving.
• Build scalable infra and tooling to boost reliability and efficiency of ML workloads.
• Develop automation workflows and internal tools to reduce operational complexity.
• Architect systems enabling efficient model deployment, monitoring, and operation across environments.
• Improve workload scheduling, monitoring, and resource management for GPU and cloud infra.
• Drive observability, automation, reliability, and developer experience across the platform.

🎯 Requirements

• Strong experience building/operating production systems for reliability and performance.
• Cloud infra, Linux environments, and infrastructure automation expertise.
• Experience operating distributed systems in production, including Kubernetes.
• Strong Python programming skills (or backend languages).
• Experience building internal platforms, developer tooling, and infra abstractions.
• Knowledge of Terraform, Datadog, GitHub Actions, and observability practices.

🎁 Benefits

• Fully remote work environment with flexibility across Europe.
• Work on advanced AI infrastructure for large-scale enterprise apps.
• 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.