Infrastructure Engineer - Platform

Nvidia
Berlin, Germany
16 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Languages
German
Job source

Tech stack

Intelligent Platform Management Interface Bash Shell Border Gateway Protocol BIOS Ubuntu (Operating System) Nvidia CUDA Continuous Integration Data Centers Linux DevOps RAID Firmware
+22 more
InfiniBand Data Intelligence Python (Programming Language) Node.Js Performance Tuning Remote Direct Memory Access Red Hat Enterprise Linux Ansible Ceph (Software) Network Switches Scripting Extensible Firmware Interface Large Language Models Git Kubernetes Infrastructure Automation Frameworks Bare Metal Machine Learning Operations TensorRT Terraform Network Server Nvme

Job description

You’ll own the layer everything else runs on: bare-metal servers, operating systems, data-center networking, and storage across on-prem and fully air-gapped sites - the physical and infrastructure foundation our platform and GPU fleets are built on. You design, build, and operate server fleets with a strong automation and DevOps mindset, then partner with our SRE, MLOps, and ML teams to ensure everything running above the metal - including GPU inference - performs reliably at scale. Some of this work is hands-on at customer sites, where you size, rack, and commission self-contained server environments with no internet uplink.

We weight depth in modern data-center infrastructure, networking, and automation more heavily than GPU-specific experience. A strong infrastructure and network engineer with a genuine automation mindset - even without prior GPU exposure - is a better fit for this role than a candidate with GPU expertise whose networking background is rooted in legacy, corporate-style L2 designs., * Design, size, provision, and operate bare-metal server fleets across on-prem and air-gapped environments (firmware/BIOS/UEFI, BMC via Redfish/IPMI, OS, RAID, kernel and storage tuning) using zero-touch provisioning (PXE/iPXE, MAAS/Metal3/Tinkerbell/Ironic) and automation (Ansible, Terraform, or equivalent - the tooling matters less than the automation mindset).

  • Build and run modern data-center networking: L2/L3 design, IP Fabric, BGP and switching, and RDMA fabrics (RoCE/InfiniBand) sized to scale without ripping out the core.
  • Engineer resilient, highly available storage (Ceph/Rook, NVMe) with capacity planning and encryption at rest.
  • Operate confidently in air-gapped and on-prem environments: offline mirrors and registries, signed artifacts, firmware/driver lifecycle without internet access, and system hardening.
  • Support MLOps and inference-serving fundamentals - GPU model serving (Triton/KServe/vLLM), GPU scheduling and sharing, and throughput/latency optimization - in partnership with our SRE and ML teams.
  • Plan and run on-site build-outs: rack integration, power budgets, thermal/cooling and UPS sizing, commissioning, capacity planning, runbooks, and operator handover, with SWaP awareness for field sites.

Requirements

  • 5+ years in bare-metal, data-center, or systems infrastructure engineering, with hands-on ownership of physical and compute infrastructure at scale.
  • Strong bare-metal Linux (Ubuntu, RKE2, Talos, or similar): provisioning, firmware/BMC management, PXE/iPXE, kernel and storage tuning, systemd, RAID.
  • Real experience with infrastructure automation (Ansible, Terraform, or equivalent), Git and CI/CD, and scripting in Python, Bash, or Go.
  • Solid, current data-center networking fundamentals: L2/L3, IP Fabric, BGP, and switching - this is a hard requirement, not a nice-to-have. RDMA (RoCE/InfiniBand) experience is a strong plus.
  • Comfortable operating in air-gapped or on-prem environments and traveling to customer sites for builds and deployments.
  • Practical hardware sizing literacy: power budgets, thermal/cooling, UPS sizing, and rack integration.
  • Documentation-focused, methodical, and calm during hardware incidents. Eligible to work in Germany., * German language (B1+); exposure to regulated or security-critical environments (e.g. BSI C5, ISO 27001, or defense-sector delivery) is a plus.
  • NVIDIA GPU stack knowledge (drivers, CUDA, GPU Operator, MIG, DCGM) and cross-node GPU interconnect experience (NVLink, InfiniBand, NCCL).
  • Kubernetes bare-metal fundamentals - how cluster bring-up and GPU device plugins interact with the underlying hardware, not day-to-day cluster operation.
  • Inference optimization (vLLM, TensorRT-LLM, quantization) and familiarity with switch NOS (SONiC/Cumulus).
  • Relevant certifications (NVIDIA, Red Hat, CKA/CKS) or field/forward-deployed engineering experience.

About the 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.

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