ML Platform Engineer

📋 Description

• Design, build, and improve ML platform systems for training, deployment, and serving.
• Build scalable infra and tooling to improve reliability, efficiency, and cost of ML workloads.
• Develop automation, internal tools, and agent-oriented systems to reduce ops for researchers.
• Architect and maintain deployment, monitoring, and operation across research and product environments.
• Improve workload scheduling, monitoring, and resource management for GPU-based and cloud infra.

🎯 Requirements

• Strong production systems experience focusing on reliability, scalability, performance, and maintainability.
• Hands-on cloud infrastructure, Linux, and infrastructure automation.
• Production distributed systems experience including Kubernetes-based workloads.
• Strong Python or backend programming skills.
• Experience with Terraform, Datadog, and GitHub Actions.
• Experience with ML infrastructure, model serving, or data-heavy workloads.

🎁 Benefits

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