(GPU) Infrastructure Engineer

Stellenbeschreibung:

Orcrist is building a next generation data intelligence platform using cutting-edge technologies. We’re handling petabyte-scale data with sub-second queries. Our product is a Kubernetes-based platform delivered as B2B SaaS or as a self-hosted on-prem solution, including air-gapped deployments. We enable customers across defense, law enforcement, and enterprise to turn mission-critical data into actionable intelligence. Our Platform team owns the infrastructure that powers every deployment, from the metal up.

Infrastructure Engineer – Platform

Role

Kubernetes runs on something, and that something is yours. You’ll own the layer beneath our platform: bare-metal GPU servers, operating systems, networking, and storage across on-prem and fully air-gapped sites. You design, build, and operate GPU server fleets and the NVIDIA software stack, then partner with our SRE and ML teams to deliver fast, reliable on-prem inference. Some of this work is hands‑on at customer sites, where you size, rack, and commission self‑contained server environments that run with no internet uplink.

What you’ll do

  • Design, size, provision, and operate bare-metal GPU server fleets across on‑prem and air-gapped environments (firmware/BIOS, BMC via Redfish/IPMI, OS, drivers) with zero‑touch provisioning (PXE/iPXE, MAAS/Metal3/Tinkerbell) and automation (Ansible/Salt, Terraform/Pulumi).
  • Own the NVIDIA GPU stack end to end: drivers, CUDA, GPU Operator, Container Toolkit, MIG, and DCGM, tuned for inference throughput, latency, and utilization.
  • Build the bare‑metal substrate Kubernetes runs on: node lifecycle, container runtime, GPU device plugins, node feature discovery, and kernel/NUMA tuning.
  • Engineer data‑center networking and resilient storage (VLANs/switching, RDMA, Ceph/ZFS/NVMe) sized to scale without replacing the core, with encryption at rest.
  • Partner with ML and MLOps on on‑prem inference serving (Triton, KServe, vLLM): model deployment, GPU scheduling and sharing, and performance tuning.
  • Plan and run on‑site build‑outs: rack integration, power/UPS and cooling sizing, commissioning, capacity planning, runbooks, and operator handover.

About You

  • 5+ years in bare‑metal, HPC/GPU, data‑center, or systems infrastructure engineering, with hands‑on ownership of physical and compute infrastructure.
  • Strong bare‑metal Linux (RHEL/Rocky/Ubuntu): firmware, BMC, PXE, kernel and storage tuning, plus solid networking and storage fundamentals.
  • Real experience with the NVIDIA GPU stack (drivers, CUDA, GPU Operator, MIG, DCGM) and serving GPU models in production.
  • Comfortable operating in air‑gapped or on‑prem environments and traveling to customer sites for builds and deployments.
  • Documentation‑focused, methodical, and calm during hardware incidents.
  • Ideally with a B driver's license.
  • Eligible to work in Germany.

Nice‑to‑haves

  • German language (B1+)
  • NVIDIA DGX/HGX or Slurm experience
  • InfiniBand/RDMA fabrics, and inference optimization (TensorRT-LLM, vLLM, quantization)
  • Certifications such as NVIDIA NCP-AIO, Red Hat RHCSA/RHCE, or CKA/CKS.
  • Field‑engineering experience and familiarity with secure or regulated deployment environments.

What We Offer

  • Modern architecture & stack.
  • Remote‑first in Germany with occasional team events in Berlin.
  • Home office budget and great equipment.
  • 30 days vacation.
  • Direct impact on critical missions across private and public‑sector customers.

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Stelleninformationen

  • Veröffentlichungsdatum:

    03 Aug 2026
  • Standort:

    Berlin
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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