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.Skills Required
- Bachelor’s or master’s degree in Computer Science, or equivalent experience
- 6+ years of infrastructure engineering experience
- Strong configuration management experience with Ansible, Salt, Puppet, Chef, or comparable tools
- Experience with GitOps practices at scale, including review workflows, environment promotion, drift detection, and safe rollback
- Proficiency in Go, Python, and shell
- Experience building infrastructure automation tooling
- Experience automating stateful, long-lived infrastructure that cannot simply be destroyed and recreated
- Experience bringing a manually administered production estate under configuration management
- Familiarity with LSF, Slurm, or another batch scheduler
- Infrastructure CI/CD experience, including production-like test environments
- Observability and instrumentation experience for automated systems
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
