Sr Software Engineer - Distributed Systems Engineer, EDA Infrastructure NVIDIA is hiring engineers to build and scale the infrastructure that supports our Electronic Design Automation (EDA) workloads. We are looking for 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 help design reliable automation and platform services that manage large fleets of GPU-based and CPU-based compute systems used by engineering teams across NVIDIA. The ideal candidate is comfortable working across software, operating systems, cluster schedulers, networking, storage, and physical hardware. You should enjoy solving complex operational problems, eliminating repetitive work through automation, and building systems that remain reliable as infrastructure grows. If you are creative, pragmatic, and motivated to improve how critical engineering workloads are delivered, we would like to hear from you. What You Will Be Doing: Design and build platforms that automate the provisioning, configuration, operation, and lifecycle management of large-scale GPU and CPU compute infrastructure. Develop monitoring, health-management, and remediation systems that improve the reliability, availability, and utilization of EDA compute environments. Automate hardware deployment, operating-system 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 hardware diagnostics, operating-system signals, scheduler data, and network and storage telemetry to identify
Senior Infrastructure Automation Engineer, Compute Platform - EDA Infrastructure
Salary not disclosed
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Role overview
Job description
Managing twenty-five scheduler cells by hand does not scale, and we are not going to try. NVIDIA is building a config-as-code foundation for its EDA compute farm, and we need an automation engineer to own it end to end. You are joining at the point where this is still partially manual and inconsistently applied across cells. That is the interesting version of the problem — you will be migrating off partial systems and reconciling drift, not starting from a blank repository.
What you'll be doing:
Designing and owning the configuration schema for LSF cell deployment, so that a policy change is written once, reviewed, tested, and applied identically everywhere it belongs.
Building the deployment pipeline that takes scheduler configuration from merge to production across a federated estate, including staged rollout and rollback.
Eliminating configuration drift across cells, and building the tooling that keeps it eliminated.
Standing up the regression suite that lets us upgrade LSF on a schedule rather than on a dare.
Working alongside our LSF internals engineer to encode hard-won scheduler knowledge into templates and policy, so that expertise lives in the repository instead of in one person's head.
What we need to see:
BS or MS in Computer Science or equivalent experience.
6+ years in infrastructure engineering with strong config management depth — Ansible, Salt, Puppet, Chef, or comparable.
Real experience with GitOps practice at scale: review workflow, environment promotion, drift detection, and safe rollback.
Proficiency in Go, Python and shell, and comfort building the tooling rather than only using it.
Experience automating stateful, long-lived infrastructure where you cannot simply destroy and recreate.
Ways to stand out from the crowd:
You have brought a manually administered estate under configuration management while it stayed in production.
Familiarity with LSF, Slurm, or another batch scheduler as a configuration target.
CI/CD experience for infrastructure, including test environments that meaningfully resemble production.
Observability instincts — you instrument what you automate.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.What they are looking for
Skills & requirements
Hiring company
NVIDIA
We create the world’s fastest supercomputer and largest gaming platform.
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