# \(GPU\) Infrastructure Engineer - Company: [Orcristtechnologies]() - Location: Remote / Berlin - Remote: Yes - Team: Engineering - Posted: June 17, 2026 ## Job description ## Infrastructure Engineer – Platform ### Company 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. ### 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. ## Apply [Apply on Orcristtechnologies]() Canonical job page: