Compute Infrastructure Engineer

📋 Job Overview

As Compute Infrastructure Engineer – NeuraGym, you will work at the interface of server architecture, virtualization, container orchestration, and data processing, with a particular focus on building a scalable compute and storage infrastructure for multimodal robotics data. Your core task is to design, build, and operate the system landscape in NeuraGym, ensuring that recording and processing of large data volumes run reliably, performantly, and reproducibly.

🏢 About Neura Robotics GmbH

Neura Robotics GmbH is a company focused on embodied AI systems, developing innovative solutions at the intersection of robotics and artificial intelligence.

🎯 The Role

You will play a crucial role in developing high-quality embodied AI systems by connecting individual servers, workstations, and edge devices into a distributed, maintainable, and scalable compute system.

✅ Key Responsibilities

• Infrastructure planning: Plan and dimension the NeuraGym server infrastructure, including compute, GPU, storage, and network, rack layout, power and cooling concepts, and procurement in coordination with the team.
• Virtualization: Build and operate virtualization environments based on hypervisors like Proxmox and provide development, test, and production environments.
• Kubernetes & GPU-Scheduling: Design and operate Kubernetes clusters (or comparable orchestration) for data preprocessing, including GPU-scheduling, monitoring, and logging.
• Distributed processing: Distribute compute- and data-intensive processes intelligently across multiple machines, from edge devices on robots to local servers and central storage systems, ensuring bottlenecks are identified and eliminated.
• Network design: Design the network infrastructure of NeuraGym: VLANs, switching, bandwidth planning for camera and sensor streams, firewall rules, and secure integration into the rest of the corporate IT.
• Storage & data pipelines: Build storage and data pipelines for large data volumes (e.g., object storage, distributed file systems, streaming ingestion) and ensure data is reliably captured, stored, versioned, and available for model training.
• Automation: Automate provisioning, deployment, and operation with Infrastructure-as-Code and CI/CD tools and document the system landscape comprehensibly.
• Stability & security: Identify and resolve performance, stability, and security issues in the infrastructure and develop backup, recovery, and access concepts.

📌 Required Qualifications

• Education: Degree in Computer Science, Systems Engineering, Engineering, or a related field, or a comparable vocational training with relevant practical experience.
• Experience: 4+ years of experience in System Administration, Infrastructure Engineering, DevOps, or Platform Engineering.
• Server infrastructure: Solid experience in planning, design, and operation of server infrastructure (sizing, rack setup, hardware selection, procurement).
• Virtualization: Practical experience with hypervisors and virtualization (e.g., Proxmox, KVM, VMware), including storage and network integration.
• Container: In-depth knowledge of container technologies and orchestration (Docker, Kubernetes, or comparable platforms), ideally with GPU workloads.
• Distributed systems: Understanding of how processes, data, and compute load can be meaningfully distributed, synchronized, and monitored across multiple machines.
• Linux & scripting: Proficient with Linux systems, shell scripting, and at least one scripting language (e.g., Python, Bash).
• IaC & CI/CD: Experience with Infrastructure as Code and automation (e.g., Ansible, Terraform) as well as CI/CD tools (e.g., GitLab CI).
• Work style: A structured, independent work style and enjoyment of building infrastructure from the ground up together with an interdisciplinary team.

⭐ Desirable Experience

• Experience with monitoring and logging stacks (e.g., Prometheus, Grafana).

🎁 Benefits

Competitive