Vultr
GPU Fabric Engineer
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USARemotegpunetworkingcloudfabric
Responsible for validating, troubleshooting, and optimizing high-speed networking fabrics for GPU clusters powering AI training and inference.
About the company
- 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.
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
Requirements
- 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
Conditions
- $125,000 - $135,000
- Final compensation will vary depending on years of experience, background/skill set, location, and applicable laws.
Other
- 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
- 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 Infrastru
- We are an equal opportunity employer and are committed to creating an inclusive environment for all employees. We welcome applications from individuals of all backgrounds and experiences, and we prohibit discrimination based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status under applicable laws. Vultr will consider qualified applicants with arrest or conviction records in accordance with applicable laws and will not conduct a background check until after an offer of employment has been extended and accepted.
- We also take your privacy seriously. We handle personal information responsibly and follow applicable laws, including U.S. privacy rules and India’s Digital Personal Data Protection Act, 2023. Your data is used only for legitimate business purposes and is protected with proper security measures.
- Where allowed by law, applicants may request details about the data we collect, access or delete their information, withdraw consent for its use, and opt out of nonessential communications. For more details, please see our Privacy Policy .