Senior Infra Engineer: Scale GPU/CPU Compute & Automation

NVIDIA Gruppe; Washington; On-site; USD 180,000 - 288,000; Full time

Job summary

NVIDIA is hiring engineers to build and scale the infrastructure that supports EDA workloads. We seek engineers with strong programming skills, a deep understanding of distributed systems, experience operating large-scale production infrastructure, and excellent communication and planning abilities.

You will design automation and platform services for GPU/CPU compute fleets used by NVIDIA teams across the company, collaborating across EDA, infrastructure, networking, storage, and hardware groups

Qualifications

• 5+ years of software or infrastructure engineering for large-scale production systems.
• Strong programming in Go or Python and solid CS fundamentals.
• Experience designing automation for distributed Linux compute fleets.
• Excellent cross-team communication and ownership mindset.

Responsibilities

• Design and build platforms to automate provisioning and lifecycle of GPU/CPU compute infrastructure.
• Develop monitoring, health-management, and remediation systems to improve reliability and utilization.
• Automate hardware deployment, OS configuration, firmware and software updates, cluster enrollment, and recovery workflows.
• Build reliable services and workflows that integrate with schedulers, infra management, and observability platforms.
• Use telemetry to identify failures and return unhealthy systems to service.
• Work with EDA, infrastructure, networking, storage, and hardware teams to deliver scalable solutions.
• Participate in incident response, root-cause analysis, capacity planning, and continuous improvement.

Skills

Go or Python

Distributed systems

Large-scale infra

Communication skills

Ownership mindset

Education

BS in CS/Engineering/Physics/Math

Tools

Slurm

LSF

Kubernetes

Bright Cluster Manager

Job description

NVIDIA is hiring engineers to build and scale the infrastructure that supports EDA workloads. We seek engineers with strong programming skills, a deep understanding of distributed systems, experience operating large-scale production infrastructure, and excellent communication and planning abilities.

You will design automation and platform services for GPU/CPU compute fleets used by NVIDIA teams across the company, collaborating across EDA, infrastructure, networking, storage, and hardware groups