Senior Platform Engineer – Cloud & ML Platform (m/f/d)

Job summary

As a Platform Engineer for Cloud & ML Platform, you will design, deploy, and improve Kubernetes-based platforms for machine learning workloads, collaborating with various teams to provide robust infrastructure.

Benefits

Qualifications

• Expertise with Kubernetes in production environments.
• Experience deploying and maintaining large-scale clusters.
• Experience with Kubeflow and Metaflow in ML environments.
• Understanding of MLOps workflows and deployment automation.
• Experience with GPU-enabled Kubernetes environments.
• Infrastructure-as-code experience with tools like Terraform and Ansible.
• Understanding of cloud-native observability.
• Experience with containerization and CI/CD processes.
• Familiarity with cloud platforms like Azure and AWS.
• Scripting skills in Python, Go, or Bash.
• Ability to analyze infrastructure issues and implement solutions.
• Structured mindset with a strong sense of ownership.
• Strong communication skills for collaboration with teams.
• Proficient in English.

Responsibilities

• Design, deploy, operate, and improve Kubernetes-based platforms for machine learning workloads.
• Build and maintain globally distributed Kubernetes clusters focusing on reliability and security.
• Manage lifecycle of ML platform components including Kubeflow and Metaflow.
• Enable AI teams to run scalable training and data processing pipelines.
• Develop infrastructure-as-code and automation workflows.
• Manage GPU workloads and resource utilization.
• Improve platform resilience through monitoring and incident response.
• Collaborate with teams to define platform standards and best practices.
• Support hybrid and multi-cloud infrastructure scenarios.
• Evaluate and integrate cloud providers and technologies.
• Enhance developer experience for ML engineers.
• Facilitate transition of AI capabilities from prototype to production.

Skills

Relocation