Member of Technical Staff - Datacenter Networking

Prime-Intellect; San Francisco (CA); On-site; USD 150,000 - 300,000; Full time

Job summary

Prime Intellect is building the open frontier AI stack and seeks a network architect to design and operate GPU cluster networks. You will own reliability for training fabrics, storage networks, and management connectivity to scale distributed workloads without bottlenecks.

You will deploy scalable datacenter topologies, configure InfiniBand/RoCE, automate provisioning, and build monitoring with ML teams to meet performance targets across large GPU clusters.

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.

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

Skills

Datacenter networking

Ethernet

TCP/IP

Routing

Switching

Redundant network design

InfiniBand/RoCE

Network troubleshooting

Automation with Python/Ansible

Leaf-spine architectures

BGP/ECMP

VLANs

Network segmentation

RDMA concepts

Linux networking

NIC drivers

Packet capture

Throughput/latency testing

Optics/transceivers

Change management

Tools

Python

Ansible

Job description

Own Your Intelligence

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.

Role Impact

You’ll design and operate the networks that connect large GPU clusters. Own the reliability and performance of training fabrics, storage networks, and management connectivity so distributed workloads can scale without the network becoming the bottleneck.

Core Technical 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

Required Experience

• 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

Infrastructure Skills

• Leaf-spine architectures, BGP, ECMP, VLANs, and network segmentation

• RDMA concepts and performance tuning; congestion control and lossless Ethernet considerations

• Linux networking, NIC drivers and firmware, packet capture, and throughput/latency testing

• Optics, transceivers, cable management, and link-level diagnostics

• Safe change management, configuration versioning, telemetry, and alerting

Nice to Have

• Experience operating 400G/800G networks or large multi-rack GPU clusters

• NVIDIA Spectrum or Quantum networking experience

• NCCL performance analysis and distributed training troubleshooting

• EVPN/VXLAN, SONiC, or network source-of-truth systems

• Experience with network simulation, automated validation, and capacity planning

Growth Opportunity

You’ll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You’ll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.

We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.

Compensation

Cash compensation range of $150,000 - $300,000 plus equity incentives.