Compute Infrastructure Engineer – NeuraGym (human)

Job summary

Designs, builds, and operates scalable compute and storage infrastructure for recording and processing multimodal robot data, connecting servers, workstations, and edge devices into a reliable distributed system for embodied AI. The role covers server and network planning, virtualisation, Kubernetes and GPU scheduling, distributed processing, and high-volume data pipelines. It also automates provisioning and operations and improves infrastructure performance, stability, security, backup, and recovery.

Qualifications

• Degree in computer science, systems engineering, engineering, or a related field, or comparable vocational training with relevant practical experience.
• At least four years of experience in system administration, infrastructure engineering, DevOps, or platform engineering.
• Experience planning, designing, and operating server infrastructure, including sizing, rack build-out, hardware selection, and procurement.
• Hands-on experience with hypervisors and virtualisation, including storage and network integration.
• Strong knowledge of container technologies and orchestration, ideally including GPU workloads.
• Understanding of distributing, synchronising, and monitoring processes, data, and compute loads across multiple machines.
• Confident Linux administration, shell scripting, and experience with at least one scripting language such as Python or Bash.
• Experience with infrastructure as code, automation, and CI/CD tooling.
• Structured, self-directed working style and interest in building infrastructure from the ground up with an interdisciplinary team.

Responsibilities

• Plan and design server infrastructure, including compute, GPU, storage, and network capacity, rack layout, power, cooling, and procurement.
• Build and operate virtualisation environments for development, testing, and production.
• Design and operate Kubernetes clusters or comparable orchestration platforms for data preprocessing, including GPU scheduling, monitoring, and logging.
• Distribute compute- and data-intensive workloads across robot edge devices, local servers, and central storage, identifying and resolving bottlenecks.
• Design network infrastructure, including VLANs, switching, bandwidth for camera and sensor streams, firewall rules, and secure IT integration.
• Build high-volume storage and data pipelines that reliably capture, store, version, and provide data for model training.
• Automate provisioning, deployment, and operations with infrastructure-as-code and CI/CD tools, and document the system landscape.
• Resolve infrastructure performance, stability, and security issues and develop backup, recovery, and access concepts.

Skills

Degrees

Industry

Relocation