• Design, build, and operate scalable ML infrastructure on GCP (GKE), supporting both experimentation and production workloads for LLMs and NLP systems. • Manage Kubernetes-based environments (GKE): deployment, scaling, upgrades, and reliability of training and inference workloads across GPU/TPU/CPU pools. • Build and maintain CI/CD pipelines (GitHub Actions, Jenkins) to automate testing, training, and deployment of ML services and infrastructure. • Implement infrastructure as code (Terraform, Ansible) to provision and manage cloud resources in a reproducible, secure, and cost-efficient way. • Ensure observability of ML systems: monitoring, logging, and alerting for infrastructure, pipelines, and production inference workloads. • Collaborate with ML engineers and Data Engineers to design and support reliable training and inference pipelines. • Optimize resource utilization and cost, improving efficiency of training and serving infrastructure. • Troubleshoot and resolve issues across the ML platform - from data pipelines to distributed training and production deployments. • Contribute to engineering best practices: code reviews, automation, and continuous improvement of platform reliability and developer experience.

• Become a member of a highly collaborative engineering team offering a unique blend of Cloud Infrastructure Administration, Site Reliability Engineering, Security Operations, and Vulnerability Management across multiple clients. • Coordinate with client product teams, engineering team members, and other stakeholders to monitor and maintain a secure and resilient cloud-hosted infrastructure to established SLAs in both production and non-production environments. • Innovate and implement using automated orchestration and configuration management techniques. Understand the design, deployment, and management of secure and compliant enterprise servers, network infrastructure, boundary protection, and cloud architectures using Infrastructure-as-Code. • Create, maintain, and peer review automated orchestration and configuration management codebases, as well as Infrastructure-as-Code codebases. Maintain IaC tooling and versioning within Client environments. • Implement and upgrade client environments with CI/CD infrastructure code and provide internal feedback to development teams for environment requirements and necessary alterations. • Work across AWS, Azure and GCP, understanding and utilizing their unique native services in client environments. • Configure, tune, and troubleshoot cloud-based tools, manage cost, security, and compliance for the Client’s environments. • Monitor and resolve site stability and performance issues related to functionality and availability. • Work closely with client DevOps and product teams to provide 24x7x365 support to environments through Client ticketing systems. • Support definition, testing, and validation of incident response and disaster recovery documentation and exercises. • Participate in on-call rotations as needed to support Client critical events, and operational needs that may lay outside of business hours. • Support testing and data reviews to collect and report on the effectiveness of current security and operational measures, in addition to remediating deviations from current security and operational measures. • Maintain detailed diagrams representative of the Client’s cloud architecture. • Maintain, optimize, and peer review standard operating procedures, operational runbooks, technical documents, and troubleshooting guidelines

• Develop and maintain cost allocation, budgeting, and chargeback models across cloud accounts (AWS, Azure, GCP). • Implement and enforce tagging and resource hierarchy standards, ensuring >90% coverage for cost-critical tags (e.g., Application, Environment, Cost Center). • Build and publish cost visibility dashboards and reports using Power BI, QuickSight, Looker, or other FinOps tooling. • Support unified multi-cloud cost reporting and forecasting for engineering and finance teams. • Execute rightsizing, scheduling, and lifecycle management of cloud resources across AWS, Azure, and GCP (EC2, VM, GCE, RDS, S3, Storage, Networking). • Manage and optimize Reservations, Savings Plans, Committed Use Discounts (CUDs), and licensing benefits (BYOL, AHB). • Implement policy-as-code and governance using tools like Terraform, AWS Config, Azure Policy, or GCP Organization Policies. • Participate in anomaly detection, spend forecasting, and automation of remediation workflows. • Contribute to CI/CD pipeline management, infrastructure automation, and GitOps practices using Azure DevOps, GitHub Actions, AWS CodePipeline, or Google Cloud Build. • Provide actionable insights in monthly cost and performance reviews with engineering and product stakeholders. • Partner with Finance and Procurement teams on budgeting, forecasting, and billing validation. • Collaborate with SRE and Platform teams to balance cost efficiency, performance, and reliability. • Maintain operational hygiene through scripting, compliance audits, and automation.

• verantwortlich für den Aufbau und die Verwaltung von Kubernetes-Clustern, um Container-Anwendungen zu orchestrieren • implementierst und pflegst CI/CD-Pipelines, um Entwicklungs-, Test- und Bereitstellungsprozesse zu automatisieren • arbeitest eng mit den Entwicklungsteams zusammen, um skalierbare und hochverfügbare Cloud-Infrastrukturen zu implementieren und zu optimieren • sicherstellst die Stabilität und Performance der Systeme, indem du Systemressourcen proaktiv überwachst und optimierst • unterstützt bei der Einführung und Verbesserung von DevOps-Best Practices in den Teams