Senior Platform Engineer

• Design and operate container orchestration platforms optimized for NVIDIA DGX/HGX-class hardware.
• Build bare-metal provisioning systems (PXE, Ironic, MAAS) to bring GPU clusters online at scale.
• Manage GPU lifecycle: driver stacks, CUDA/kernel compatibility, MIG slicing, and performance tuning.
• Partner with Network Engineering and DCOps to align physical infrastructure with software orchestration.
• Build automation and internal tooling in Go or Python to streamline cluster operations.
• Implement Terraform/Ansible-based IaC for fully auditable, repeatable infrastructure.
• Design high-resolution observability stacks (Prometheus/Grafana, DCGM, VictoriaMetrics).
• Participate in a specialized on-call rotation supporting GPU workloads and core platform services.

Do you have experience in Systems engineering?, Requirements: 3+ years in Systems Engineering or HPC Infrastructure, strong Linux and bare-metal GPU experience, NVIDIA DGX/HGX, InfiniBand/RoCE, and automation with Python or Go, * 7+ years in systems, platform, or distributed systems engineering (10+ for Staff).

• Expert-level Linux knowledge: kernel modules, sysctl tuning, hugepages, container runtimes.
• Hands-on experience bootstrapping Kubernetes or SLURM on physical hardware.
• Strong proficiency in Go (preferred) or Python for systems-level automation.
• Deep familiarity with NVIDIA GPU ecosystems (drivers, CUDA, MIG).
• Working knowledge of InfiniBand or RoCEv2 networking and NCCL performance tuning.
• Experience building observability pipelines for hardware-accelerated environments.
• Ability to troubleshoot complex, multi-layered issues across hardware, networking, and orchestration.
• Strong cross-team communication - you’re the “glue” between Network, DCOps, and Software.

Bonus Points

• Experience with SLURM, Kubeflow, or distributed PyTorch.
• Integrating vendor APIs (NetBox, Vault, GitLab CI, etc.) into unified workflows.
• Infrastructure testing, chaos engineering, or cluster-level integration test suites.
• Designing telemetry aggregation across hardware, networking, and environmental systems.

Pulled from the full job description

• Paid time off
• RSU, * $175k - $275k/year DOE
• RSU’s
• 5 weeks PTO
• 401k w/ match
• Comprehensive Benefit Plan

We build the high-performance, bare-metal GPU infrastructure that powers modern AI. Our team designs and operates large-scale NVIDIA DGX/HGX clusters, high-speed networking, and the automation that turns complex hardware into a reliable, production-ready platform. We work directly with the metal: provisioning nodes, tuning Linux, integrating InfiniBand/RoCE, and building the tooling that enables fast, secure, and scalable AI workloads.