System Software Engineer (gn) Cloud & Simulation

Wandelbots GmbH
Dresden, Germany
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Cloud Computing Nvidia CUDA Continuous Integration Linux DevOps Python (Programming Language) Reliability Engineering System Software Kubernetes Hardware Infrastructure

Job description

We are looking for an engineer to lead the productization and internal standardization of our simulation platform, NOVA. You will focus on the infrastructure and operational foundations, transforming our current simulation capabilities into a robust, scalable product for internal teams and external partners. Activities - Build and operate GPU infrastructure including NVIDIA GPU Operator, device plugins, and driver lifecycle - Integrate simulation workloads into shared Kubernetes and cloud infrastructure - Implement declarative deployments using Infrastructure as Code and GitOps - Own CI/CD and container/image lifecycles for CUDA- and NGC-based workloads - Design scheduling and autoscaling for interactive streaming and compute-intensive simulation jobs Requirements - Experience building or operating production systems in platform engineering, infrastructure, SRE, or DevOps - Practical Kubernetes experience including resource management and workload scheduling - Proficiency in Infrastructure as Code, GitOps, and CI/CD - Solid knowledge of Linux, containers, and networking - Strong Python skills for automation and services Team You will join our Simulation team, working closely with our established infrastructure team to own simulation-specific workloads, deployment patterns, and operational requirements. Application Process Screening Call, remote, with Recruiter (30 min) Follow-Up Interview, remote, with Hiring Manager / CRO (45 min) Onsite Interview with Stakeholder Interviews, Product Demo and Live Exercise (appr. 4h)

Requirements

Experience building or operating production systems in platform engineering, infrastructure, SRE, or DevOps

  • Practical Kubernetes experience including resource management and workload scheduling
  • Proficiency in Infrastructure as Code, GitOps, and CI/CD
  • Solid knowledge of Linux, containers, and networking
  • Strong Python skills for automation and services

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