System Software Engineer (gn) Cloud & Simulation

Responsibilities

We are representing a confidential robotics technology organization in Dresden that needs a systems-focused engineer to productize their simulation infrastructure. You will transform internal prototypes into production-ready platforms that can be operated independently by multiple teams and external partners.

Your work will include:

• Building and operating GPU infrastructure for simulation workloads, including NVIDIA GPU Operator, device plugins, driver lifecycle, and GPU sharing through MIG or time slicing
• Integrating simulation workloads into shared Kubernetes and cloud infrastructure in close collaboration with the platform team
• Making deployments declarative and reproducible using Infrastructure as Code and GitOps approaches
• Owning CI/CD pipelines and container lifecycle for CUDA and NGC-based workloads
• Designing scheduling and autoscaling for both latency-sensitive interactive streaming sessions and compute-intensive processing jobs
• Turning a Gaussian Splatting pipeline into a reproducible workflow from data capture through training to OpenUSD assets
• Operating and extending an Omniverse and Isaac Sim streaming platform, including Kit App Streaming, session lifecycle, and tenant isolation
• Establishing the platform as an internal standard through self-service workflows, documentation, and golden-path templates
• Preparing the solution for external operation through packaged deployments, versioned releases, upgrade paths, and actionable diagnostics
• Supporting deployments across cloud, on-premises, and partner-managed environments
• Building observability using metrics, logs, GPU telemetry, and actionable alerting
• Defining security and access models including ingress, TURN and STUN for WebRTC, RBAC, secrets management, SSO, and tenant boundaries
• Collaborating with robotics, product, and platform teams to ensure the solution supports real development workflows

What We're Looking For

Our client seeks an engineer interested in how complex systems are built, deployed, and operated—not just delivering application features.

Required experience and skills:

• Production systems experience in platform engineering, infrastructure, SRE, DevOps, or systems software
• Practical Kubernetes experience including resource management, workload scheduling, and debugging distributed systems under load
• Experience with Infrastructure as Code, GitOps, and CI/CD, with the ability to evaluate tools based on problem requirements
• Solid knowledge of Linux, containers, and networking
• Strong Python skills for automation, services, and data-processing workflows
• Either experience with GPU workloads or a strong technical foundation with clear interest in working with drivers, CUDA, and GPU scheduling
• Ability to turn working technology into systems that other teams can use independently
• Strong operational ownership including documentation, diagnostics, maintainability, and reproducibility
• Very good English; German is a plus

Nice to have:

• Experience turning internally developed systems into products for customer-controlled environments
• Hands-on experience with NVIDIA Omniverse, Isaac Sim, Kit SDK, or OpenUSD
• Experience with Gaussian Splatting, NeRF, photogrammetry, or comparable 3D reconstruction pipelines
• Knowledge of WebRTC, pixel streaming, or other low-latency video technologies
• Python, Rust, or Go skills sufficient to contribute to existing services and infrastructure tooling
• Experience with robotics or simulation such as ROS 2 or sim-to-real workflows
• Experience with multi-tenant platforms, air-gapped deployments, or customer environments with specific security and compliance requirements

Our client does not expect candidates to have prior experience with every technology listed. A strong systems foundation, ability to learn unfamiliar components, and genuine interest in this problem space matter more than matching every item.

How We Work With You

When you apply through Get A Job.ai, our talent team will review your profile and conduct an initial screening. If there's a strong match, we'll submit your candidacy to our client for consideration. Please do not contact the employer directly—all communication flows through our recruiting process to ensure the best experience for everyone involved.

Pay

Compensation details will be discussed during the screening process based on your experience and the client's budget for this role.

Equal Employment Opportunity: Get A Job.ai is committed to inclusive recruiting practices. We evaluate all candidates based on qualifications and professional merit.