[Remote] AI Infrastructure Engineer at Hydra Host
Note: The job is a remote job and is open to candidates in USA. Hydra Host is a Founders Fund–backed NVIDIA cloud partner building the infrastructure platform that powers AI at scale. As an AI Infrastructure Engineer, you will work directly with AI platform customers to optimize their infrastructure on Hydra, focusing on Kubernetes clusters, GPU configurations, and automating the onboarding process.
Responsibilities
• Get AI Platform customers production-ready on Hydra —standing up Kubernetes clusters, configuring GPU drivers, validating networking, and troubleshooting the issues that surface when real workloads hit real hardware
• Own the bare metal ←→ platform layer —bridging GPU infrastructure (NCCL, InfiniBand, NVLink, storage) with orchestration layers (Kubernetes, SLURM) and MLOps tooling that customers actually use
• Configure, benchmark, and debug NVIDIA driver stacks —firmware versions, CUDA compatibility, NCCL tuning, MIG configurations. Run quality benchmarks and diagnostics to validate performance for inference and training workloads across chip types
• Identify gaps before customers do —pressure-testing Hydra's infrastructure, APIs, and workflows to find what's missing or broken
• Turn customer learnings into product —working with Product and Engineering to build reusable templates, default configurations, and automated workflows that eliminate manual onboarding
• Advise customers on chip selection and tokenomics —helping AI platform customers understand price/performance trade-offs across GPU types, cost-per-token economics, and which hardware fits their inference or training workloads
Skills
• Bare metal Linux depth — you've administered GPU servers at the metal: driver stacks, kernel tuning, firmware, storage configuration. Not just managed K8s
• NVIDIA GPU stack expertise — drivers, CUDA, NCCL, NVLink, nvidia-smi profiling. You understand how stack compatibility affects performance
• Kubernetes and orchestration — production experience with K8s, SLURM, or similar. You know how to stand up clusters, not just deploy to them
• AI Networking fundamentals — TCP/IP, VLANs, bonding, and high-speed interconnects (InfiniBand, RoCE) for distributed workloads
• Customer-facing communication — you can work directly with engineers at AI platform companies, understand their constraints, and translate that into clear requirements for your team
• Bias toward scalable solutions — you'd rather build a feature that helps 10 customers than a custom deployment that helps 1
• HPC or large-scale distributed training environments
• AI workload experience (vLLM, PyTorch, inference frameworks)
• Storage systems (NVMe, distributed filesystems, CEPH, WEKA)
• IaC and provisioning tools (Terraform, Ansible, Cloud-init, MaaS)
Benefits
• Equity ownership — meaningful stake in what we're building
• Healthcare — medical, dental, vision for you and your family
• Remote-first — with hubs in Phoenix, Boulder, and Miami
• Direct impact — your work shapes how GPU infrastructure gets deployed across the AI ecosystem
Company Overview
• Hydra offers a bare metal GPU platform, connecting businesses to a vareity of independent but standardized AI Factory Franchises. It was founded in 2021, and is headquartered in Miami, Florida, USA, with a workforce of 11-50 employees. Its website is https://www.hydrahost.com.
Apply Now
Apply Now
Responsibilities
• Get AI Platform customers production-ready on Hydra —standing up Kubernetes clusters, configuring GPU drivers, validating networking, and troubleshooting the issues that surface when real workloads hit real hardware
• Own the bare metal ←→ platform layer —bridging GPU infrastructure (NCCL, InfiniBand, NVLink, storage) with orchestration layers (Kubernetes, SLURM) and MLOps tooling that customers actually use
• Configure, benchmark, and debug NVIDIA driver stacks —firmware versions, CUDA compatibility, NCCL tuning, MIG configurations. Run quality benchmarks and diagnostics to validate performance for inference and training workloads across chip types
• Identify gaps before customers do —pressure-testing Hydra's infrastructure, APIs, and workflows to find what's missing or broken
• Turn customer learnings into product —working with Product and Engineering to build reusable templates, default configurations, and automated workflows that eliminate manual onboarding
• Advise customers on chip selection and tokenomics —helping AI platform customers understand price/performance trade-offs across GPU types, cost-per-token economics, and which hardware fits their inference or training workloads
Skills
• Bare metal Linux depth — you've administered GPU servers at the metal: driver stacks, kernel tuning, firmware, storage configuration. Not just managed K8s
• NVIDIA GPU stack expertise — drivers, CUDA, NCCL, NVLink, nvidia-smi profiling. You understand how stack compatibility affects performance
• Kubernetes and orchestration — production experience with K8s, SLURM, or similar. You know how to stand up clusters, not just deploy to them
• AI Networking fundamentals — TCP/IP, VLANs, bonding, and high-speed interconnects (InfiniBand, RoCE) for distributed workloads
• Customer-facing communication — you can work directly with engineers at AI platform companies, understand their constraints, and translate that into clear requirements for your team
• Bias toward scalable solutions — you'd rather build a feature that helps 10 customers than a custom deployment that helps 1
• HPC or large-scale distributed training environments
• AI workload experience (vLLM, PyTorch, inference frameworks)
• Storage systems (NVMe, distributed filesystems, CEPH, WEKA)
• IaC and provisioning tools (Terraform, Ansible, Cloud-init, MaaS)
Benefits
• Equity ownership — meaningful stake in what we're building
• Healthcare — medical, dental, vision for you and your family
• Remote-first — with hubs in Phoenix, Boulder, and Miami
• Direct impact — your work shapes how GPU infrastructure gets deployed across the AI ecosystem
Company Overview
• Hydra offers a bare metal GPU platform, connecting businesses to a vareity of independent but standardized AI Factory Franchises. It was founded in 2021, and is headquartered in Miami, Florida, USA, with a workforce of 11-50 employees. Its website is https://www.hydrahost.com.
Apply Now
Apply Now