Senior Distributed Systems Engineer — EDA Infrastructure

NVIDIA Corporation; California; On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Sr Software Engineer - Distributed Systems Engineer, EDA Infrastructure in California to design and scale automation for large GPU/CPU compute fleets used by engineering teams. You will build platforms for provisioning, config, and lifecycle management, and develop monitoring and remediation to improve reliability.

The role spans OS, Linux, networking, storage, and hardware considerations, requiring strong Go/Python skills and a track record of reducing operational toil

Qualifications

• BS in Computer Science, Engineering, Physics, Mathematics, or related field, or equivalent experience.
• Strong programming experience in Go or Python with data structures and algorithms.
• Experience designing automation for distributed systems and large fleets of Linux-based compute nodes.

Responsibilities

• Design and build platforms that automate provisioning, configuration, operation, and lifecycle management of large-scale GPU/CPU compute infrastructure.
• Develop monitoring, health-management, and remediation systems to improve reliability and utilization of EDA compute environments.
• Automate hardware deployment, OS configuration, firmware and software updates, cluster enrollment, and recovery workflows.
• Build reliable services and workflows that integrate with workload schedulers and observability platforms.
• Use telemetry to identify failures and return unhealthy systems to service.
• Collaborate with EDA, infrastructure, networking, storage, and hardware teams to deliver scalable solutions.

Skills

Go/Python

Distributed systems

Automation

Communication

Education

BS in CS or related field

Tools

Linux

Slurm

Kubernetes

LSF

Job description

NVIDIA is seeking a Sr Software Engineer - Distributed Systems Engineer, EDA Infrastructure in California to design and scale automation for large GPU/CPU compute fleets used by engineering teams. You will build platforms for provisioning, config, and lifecycle management, and develop monitoring and remediation to improve reliability.

The role spans OS, Linux, networking, storage, and hardware considerations, requiring strong Go/Python skills and a track record of reducing operational toil