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About the Role
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.
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
Requirements
- 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
- 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
- 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
Skills
- Ethernet
- TCP/IP
- Routing
- Switching
- Redundant network design
- InfiniBand
- RoCE
- Python
- Ansible
- Leaf-spine architectures
- BGP
- ECMP
- VLANs
- Network segmentation
- RDMA
- Lossless Ethernet
- Linux networking
- NIC drivers
- Firmware
- Packet capture
- Throughput testing
- Latency testing
- Optics
- Transceivers
- Cable management
- Link-level diagnostics
- Change management
- Configuration versioning
- Telemetry
- Alerting
- 400G/800G networks
- GPU clusters
- NVIDIA Spectrum
- NVIDIA Quantum
- NCCL
- EVPN/VXLAN
- SONiC
- Network source-of-truth systems
- Network simulation
- Automated validation
- Capacity planning
Experience Level
- 3+ years of production datacenter networking experience
Salary/Compensations
- $150,000–$300,000
About the Company
- 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.