Aimed at mid-to-senior level infrastructure engineers who enjoy designing and maintaining distributed compute systems for robotics and AI.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Neura Robotics via Ashby
YOUR MISSION & CHALLENGES
As Compute Infrastructure Engineer – NeuraGym you work at the intersection of server architecture, virtualisation, container orchestration and data processing, with a strong focus on building a scalable compute and storage infrastructure for multimodal robot data. Your core responsibility is designing, building and operating the system landscape in the NeuraGym so that recording and processing on large data volumes run reliably, performantly and reproducibly.
You play a decisive role in enabling high-quality embodied AI systems by turning individual servers, workstations and edge devices into a distributed, maintainable and extensible compute system.
- Server infrastructure planning: You plan and design the NeuraGym server infrastructure, including sizing of compute, GPU, storage and network, rack layout, power and cooling concept, and procurement in coordination with the team.
- Virtualisation: You build and operate virtualisation environments based on hypervisors such as Proxmox and provide development, test and production environments.
- Kubernetes & GPU scheduling: You design and operate Kubernetes clusters (or comparable orchestration) for data preprocessing workloads, including GPU scheduling, monitoring and logging.
- Distributed processing: You intelligently distribute compute- and data-intensive processes across multiple machines, from edge devices on the robot via local servers to central storage systems, and make sure bottlenecks are detected and removed.
- Network design: You design the NeuraGym network infrastructure: VLANs, switching, bandwidth planning for camera and sensor streams, firewall rules and secure integration with the rest of the company IT.
- Storage & data pipelines: You build storage and data pipelines for high data volumes (e.g. object storage, distributed file systems, streaming ingest) and ensure that data is reliably captured, stored, versioned and made available for model training.
- Automation: You automate provisioning, deployment and operations with infrastructure-as-code and CI/CD tooling and document the system landscape in a traceable way.
- Stability & security: You identify and resolve performance, stability and security issues in the infrastructure and develop backup, recovery and access concepts.
WHAT WE CAN LOOK FORWARD TO
- Education: Degree in computer science, systems engineering, engineering or a related field, or comparable vocational training with relevant practical experience.
- Experience: 4+ years in system administration, infrastructure engineering, DevOps or platform engineering.
- Server infrastructure: Solid experience planning, designing and operating server infrastructure (sizing, rack build-out, hardware selection, procurement).
- Virtualisation: Hands-on experience with hypervisors and virtualisation (e.g. Proxmox, KVM, VMware), including storage and network integration.
- Containers: Strong 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 are sensibly distributed, synchronised and monitored across multiple machines.
- Linux & scripting: Confident 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 tooling (e.g. GitLab CI).
- Working style: A structured, self-driven way of working and enjoyment in building infrastructure from the ground up together with an interdisciplinary team.
Nice to have: Experience with monitoring and logging stacks (e.g. Prometheus, Grafana).
Source: Neura Robotics careers (Ashby)