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Member of Technical Staff - Datacenter Networking

Prime Intellect· Engineering
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Remote$150k - $300kFull-timePosted 5d ago

About the role

Prime Intellect is building the open superintelligence stack and seeks a Technical Staff member to design and operate the networks that connect large GPU clusters, ensuring reliability and performance of training fabrics, storage networks, and management connectivity for scalable distributed workloads.

Responsibilities

  • Design and deploy scalable datacenter network topologies for GPU training, inference, storage, and management traffic
  • Configure and operate high-performance Ethernet/RoCE and InfiniBand fabrics with clear standards for routing, redundancy, and capacity
  • Automate network provisioning, configuration validation, upgrades, and rollback procedures
  • Diagnose packet loss, congestion, link failures, and collective communication performance across hosts and switches
  • Benchmark end-to-end network performance with infrastructure and ML teams, translating workload needs into measurable acceptance criteria
  • Build monitoring for port health, errors, utilization, congestion, and fabric topology; improve incident response and runbooks
  • Partner with datacenter operators and hardware vendors on cabling, optics, deployment readiness, and failure resolution

Qualifications

  • 3+ years of production datacenter networking experience
  • Strong understanding of Ethernet, TCP/IP, routing, switching, and redundant network design
  • Hands-on experience with high-performance GPU networking using InfiniBand or RoCE
  • Experience troubleshooting network problems across Linux hosts, NICs, switches, and physical links
  • Ability to automate network operations with Python, Ansible, or comparable tools

Skills

Required:Datacenter networkingInfiniBand/RoCEPython/AutomationLinux networking
Last updated Oct 21, 2026. Interested? Apply on the company site.

About Prime Intellect

Commoditizing Compute & Intelligence

Prime Intellect democratizes AI development at scale. Our platform makes it easy to find global compute resources and train state-of-the-art models through distributed training across clusters. Collectively own the resulting open AI innovations, from language models to scientific breakthroughs.

AI developmentbessemer-ai-infrastructure-2026compute resourcesdistributed trainingmodelsreinforcement-learning-platformsscience
Company profileWebsite

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