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Hut 8
Hut 8
51 – 200 Zaposleni
KriptoUmetna inteligencaWeb 3
Hut 8 builds and operates high performance computing infrastructure for Bitcoin mining and other digital workloads. Its services include hosting, managed operations, and repair for Bitcoin mining equipment, alongside computing capacity for areas such as blockchain and artificial intelligence. Hut 8’s facilities draw on varied energy sources, including renewables, and are located in cooler climates that can support efficient mining operations. The company works across crypto, AI, and Web3, bringing together infrastructure and technical teams to support the digital economy.
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Delovna mesta v podjetju

Principal AI Infrastructure Engineer

Lead GPU cluster commissioning and optimization for Highrise AI, Hut 8’s GPU-native infrastructure platform. Drive production readiness, performance validation, and Tier 3 reliability support.

USZdružene države AmerikeHibridnoPolni delovni časVodjaZahtevani Jezik: angleščinaInženir infrastrukture
AnsibleKubernetesLinuxNode.jsOblakPython

Opis

  • Bring fully installed AI clusters into production and prepare them for customer handoff.
  • Set and verify system baselines across BIOS/BMC, firmware, GPU drivers, operating systems, and cluster software.
  • Scale automated bare-metal provisioning, imaging, node configuration, and lifecycle workflows.
  • Configure and troubleshoot Linux and GPU systems, including kernels, drivers, accelerators, and host performance settings.
  • Integrate and validate Kubernetes and Slurm with platform, networking, and operations teams.
  • Run NVIDIA Field Diagnostics, L11/L12 validation, burn-in, stability checks, and hardware health qualification.
  • Analyze NCCL communication tests, GPU benchmarks, and distributed workload performance across nodes, racks, and clusters.
  • Resolve GPU, NVLink/NVSwitch, PCIe, RDMA, InfiniBand, and Ethernet performance issues.
  • Find configuration bottlenecks and improve throughput, latency, scaling efficiency, and cluster reliability.
  • Manage technical acceptance criteria, test records, defect tracking, remediation checks, and readiness recommendations.
  • Escalate and resolve complex production incidents involving compute nodes, GPU software, provisioning, scheduling, or degraded performance.
  • Investigate root causes, coordinate vendor engineering escalations, and lead corrective actions.
  • Support fleet upgrades, configuration changes, cluster expansions, and controlled post-maintenance validation.
  • Create diagnostic tools, automation, runbooks, and operational handoff materials for SRE, NOC, and site support teams.
  • Work with infrastructure engineering, site operations, OEMs, and software and platform teams to resolve cross-stack issues and meet delivery milestones.
  • Report technical status, benchmark results, risks, and acceptance recommendations to engineering leaders and stakeholders.

Zahteve

  • Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
  • At least 8 years of hands-on experience in Linux systems engineering, HPC, cloud, or large-scale infrastructure, including senior-level troubleshooting.
  • Demonstrated experience commissioning GPU or HPC clusters for production and qualifying systems against performance and reliability targets.
  • Strong skills in Linux, Python/Bash/Ansible automation, bare-metal provisioning, configuration management, and systems diagnostics.
  • Hands-on experience with NVIDIA GPU platforms, NCCL, Field Diagnostics, and multi-node performance testing.
  • Practical experience with Kubernetes and Slurm.
  • Familiarity with high-speed Ethernet, InfiniBand/RDMA, and parallel or distributed storage.
  • Ability to isolate complex issues across hardware, firmware, operating systems, and distributed workloads.
  • Methodical approach to testing, documentation, root cause analysis, and continuous improvement.
  • Ability to collaborate with experienced engineers while making and carrying out independent technical decisions.
  • Clear communication with engineering leaders, vendors, site personnel, and customer-facing stakeholders.
  • Willingness to travel to data centers for cluster commissioning, acceptance, and complex troubleshooting.
  • Flexibility to support critical incidents or maintenance outside regular business hours.

Ugodnosti

  • Directly influence the performance, reliability, and production readiness of large-scale AI clusters.
  • Work with experienced infrastructure engineers.
  • Help set technical standards for a growing global AI infrastructure platform.
  • Collaborate with colleagues from varied educational and professional backgrounds.
  • Propose new products, services, and initiatives to senior leadership.
  • Learn from team members at different career stages in a merit-based environment.
  • Build a professional network across technology, energy, and infrastructure.
  • Flexible work arrangement, hybrid or remote depending on location.

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