NVIDIA is looking for an exceptional engineer to grow and thrive alongside our CAD/EDA/HPC team. You will build and scale the compute infrastructure that powers NVIDIA's next-generation silicon — owning job scheduler environments, cloud
compute integration, CAD toolchains, and automation frameworks that keep our design teams moving at full speed toward tapeout.
What you'll be doing:
Be part of the CAD/EDA/HPC team building and scaling the compute infrastructure that powers NVIDIA's next-generation silicon design.
Own job scheduler environments, CAD toolchains, automation frameworks, and operational workflows that keep design teams moving efficiently toward tapeout.
Integrate and operate hybrid cloud environments across AWS, Azure, GCP, or OCI to elastically extend on-premises CAD capacity.
Troubleshoot CAD/EDA software and infrastructure performance issues, benchmark workloads, and improve tool and compute efficiency.
Build automation in Python, Perl, Bash, or Tcl for job scheduling, monitoring, capacity reporting, and recurring operational workflows.
Operate large-scale Linux compute farms using LSF and/or Slurm while partnering with design teams on throughput, utilization, and tapeout capacity planning.
What we need to see:
B.E./B.Tech or M.Tech/M.S. in Computer Science, Electronics Engineering, or a related field, or equivalent experience.
3+ years of hands-on experience in HPC system administration, Cloud infrastructure, Systems engineering or SRE roles supporting engineering infrastructure.
Strong Linux/Unix administration skills, large-scale compute farm experience with LSF and/or Slurm, and proficiency in at least one scripting language; Python is preferred.
Hands-on experience managing GPU nodes/compute farms
Hands-on knowledge of cloud platforms such as GCP, OCI, AWS, or Azure, including compute, storage, networking, and cost fundamentals.
Preferred exposure to Linux performance engineering, Docker/Kubernetes, infrastructure as code such as Ansible or Terraform, distributed file systems, and observability stacks.
Experience supporting the environments where CAD/EDA flows such as synthesis, place and route, simulation, DRC/LVS, or equivalent implementation and verification flows is preferred.
Skills Required
- B.E./B.Tech or M.Tech/M.S. in Computer Science, Electronics Engineering, or related field, or equivalent experience.
- 3+ years hands-on experience in VLSI CAD infrastructure, EDA compute environments, HPC system administration, or SRE roles.
- Strong Linux/Unix administration skills and large-scale compute farm experience.
- Experience with LSF and/or Slurm job schedulers.
- Proficiency in at least one scripting language (Python preferred).
- Hands-on knowledge of cloud platforms (GCP, OCI, AWS, or Azure) including compute, storage, networking, cost fundamentals.
- Good understanding of CAD/EDA flows such as synthesis, P&R, simulation, DRC/LVS, or equivalent implementation and verification flows.
- Exposure to Linux performance engineering, Docker/Kubernetes, infrastructure as code (Ansible or Terraform), distributed file systems, and observability stacks.
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.”
