GPU Fabric Engineer

## Who We Are Vultr is on a mission to make high-performance cloud infrastructure easy to use, affordable, and locally accessible for enterprises and AI innovators around the world. With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal, and Cloud Storage solutions. In December 2024 Vultr announced an equity financing at a $3.5 billion valuation. Founded by David Aninowsky and self-funded for over a decade, Vultr has grown to become the world’s largest privately-held cloud infrastructure company. **Vultr Cares** - 100% company-paid insurance premiums for employee medical, dental and vision plans. - 401(k) plan that matches 100% up to 4%, with immediate vesting - Professional Development Reimbursement of $2,500 each year - 11 Holidays + Paid Time Off Accrual + Rollover Plan - Commitment matters to Vultr! Increased PTO at 3 year and 10 year anniversary + 1 month paid sabbatical every 5 years + Anniversary Bonus each year - $500 stipend for remote office setup in first year + $400 each following year - Internet reimbursement up to $75 per month - Gym membership reimbursement up to $50 per month - Company paid Wellable subscription **Join Vultr** Vultr is seeking a highly skilled and experienced **GPU Fabric Engineer** to validate, troubleshoot, and optimize high-speed networking fabrics for GPU clusters powering large-scale AI training and inference workloads. The ideal candidate is deep hands-on experience with InfiniBand and RoCE fabrics in GPU cluster environments, and a strong understanding of how interconnect performance impacts distributed AI workloads. This is a highly visible role in a high-growth technology company, which will require expertise in fabric validation and tuning for AI workloads, the ability to diagnose complex multi-layer issues, and close collaboration with GPU engineering and networking teams. This is your opportunity to join our fast growing team and leave your mark on Vultr and the future of Cloud Infrastructure. **Key Responsibilities** - Validate and troubleshoot InfiniBand and RoCE fabrics during GPU cluster bring-up and expansion - Tune fabric performance parameters for distributed AI workloads (NCCL, MPI, collective operations) - Monitor and manage fabrics using NVIDIA UFM (Unified Fabric Manager) for health, topology, and performance visibility - Diagnose and resolve fabric-level issues including link errors, congestion, packet loss, and path asymmetry - Optimize RDMA transport settings, PFC/ECN behavior, and lossless queue configuration for GPU traffic - Validate fabric performance benchmarks and ensure line-rate throughput for AI workloads - Collaborate with GPU Engineers to correlate fabric health with workload performance - Collaborate with networking teams on fabric provisioning, configuration, and remediation - Respond to fabric alerts and degradation events across production GPU clusters - Document fabric troubleshooting procedures, tuning parameters, and validation runbooks **Qualifications** - 3–7 years of experience in network engineering, HPC fabric, or GPU infrastructure - Hands-on experience with InfiniBand and/or RoCE fabrics in GPU cluster environments - Experience with NVIDIA UFM for fabric management, monitoring, and diagnostics - Strong understanding of RDMA transport, lossless Ethernet design, and congestion management (PFC, ECN, DCQCN) - Experience with GPU cluster networking and distributed communication libraries (NCCL, MPI) - Familiarity with GPU platforms and their interconnect requirements (NVIDIA NVLink, NVSwitch, ConnectX) - Experience with fabric diagnostic tools (ibstat, ibqueryerrors, perfquery, etc.) - Proficiency in Python or Bash for scripting and validation - Basic understanding of Linux systems and server hardware - Strong troubleshooting and analytical skills across network and system layers **Compensation** $125,000 -…