Senior Distributed Systems Engineer – EDA Infrastructure

Nvidia Corporation in

Santa Clara (CA)

On-site

USD 152,000 - 288,000

Full time

6 days ago

Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA invites an experienced Senior Software Engineer to join our Distributed Systems team supporting EDA infrastructure in Santa Clara. You will design and scale automation for GPU/CPU compute fleets used by engineering teams across NVIDIA.

The role requires deep skills in distributed systems, Linux-based environments, and operations, with a focus on reliability and automation across large data centers. Equity and comprehensive benefits are provided.

Qualifications

5+ years of software engineering or infrastructure engineering experience supporting large-scale production systems.
BS in Computer Science, Engineering, Physics, Mathematics, or related field.
Strong programming experience in Go or Python, including data structures, algorithms, testing, and software design.
Experience designing automation for distributed systems and large fleets of Linux-based compute nodes.
Understanding of performance, security, reliability, fault tolerance, state management, and data consistency in complex systems.
Experience with infrastructure automation, software deployment, observability, and operational recovery.
Strong communication skills and ability to work effectively across teams, organizations, and geographic regions.
A systematic approach to problem solving, with ownership and focus on reducing operational toil.

Responsibilities

Design and build platforms that automate provisioning, configuration, operation, and lifecycle management of large-scale GPU and 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, infrastructure management systems, and observability platforms.
Use diagnostics, OS signals, scheduler data, and telemetry to identify failures and return unhealthy systems to service.
Collaborate with EDA, infrastructure, networking, storage, and hardware teams to deliver scalable solutions for chip-design workloads.
Participate in incident response, root-cause analysis, capacity planning, and production service improvement.