Role ImpactYou'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
Technical RequirementsRequired 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 OpportunityYou'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.
Apply now and join us in our mission to democratize access to planetary scale computing.
CompensationCash compensation range of $150,000-$300,000 plus equity incentives.
