Own the technical lifecycle and operational health of Runpod’s global high-density GPU fleet. Bridge hardware partners and engineering teams through hardware validation, network troubleshooting, AI-driven automation, incident response, and performance tuning for AI/ML workloads.
Salary not listed
Remote3+ YOEDevOps / SRE
About the role
Responsibilities
Assist in validating new hardware, ensuring partner deployments meet Runpod’s specifications for distributed AI/ML workloads.
Monitor fleet health to identify performance degradation. Help audit downtime and provide technical data to protect customer SLAs.
Work with LLMs and AI agents to automate network triage and generate dynamic runbooks for the fleet.
Coordinate technical incident communications with clear updates, translating outages into actionable resolutions.
Support the growth of infrastructure partners as the technical authority bridging hardware partners and internal engineering teams.
Own the technical lifecycle and operational health of the high-density GPU fleet, including HPC systems engineering, advanced network troubleshooting, and process automation.
Requirements
3–5 years of experience in infrastructure operations, systems reliability, or datacenter engineering.
Strong proficiency in datacenter networking and performance troubleshooting.
Hands-on experience with the NVIDIA Software Stack (driver installation, performance utilities) and understanding of multi-node performance tuning.
Solid Linux system administration skills and experience with containerization (Docker).
Comfortable with system-level troubleshooting and performance tuning at the kernel and hardware interface layers.
Clear written and verbal communication skills to explain hardware or networking issues to technical partners and internal leadership.
Detail-oriented and proactive in identifying potential failures before they impact customers.
Willingness to participate in an on-call rotation as the global fleet scales.
Nice-to-Haves
Experience working in a fast-paced startup environment contributing to building operational workflows.
Experience managing or optimizing bare-metal High-Performance Computing environments at massive scale.
Experience with observability tools such as Grafana, Prometheus, or Datadog.
Proficiency in Python, Go (Golang), or Bash to automate repetitive infrastructure tasks and interface with internal APIs.
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