The VLSI Productivity and Infrastructure team supports 1000+ chip design engineers with strong automation and workflows necessary to create world-changing silicon. We are building the next generation of production semiconductor design-flow infrastructure: a control-plane-driven RTL-to-GDS platform that turns design intent, configuration, generated collateral, EDA tool execution, distributed jobs, validation checks, and shared project state into observable, repeatable implementation workflows.
This role is for a senior flow/platform engineer who can work across synthesis, physical design, timing, signoff, ECO, and hierarchical execution. If you can envision and evolve legacy Tcl/Make/Perl/YAML infrastructure into a cleaner, more structured system while keeping active projects running, this role is for you!
What You'll Be Doing:
Build and modernize production RTL-to-GDS flow infrastructure across synthesis, place-and-route, timing, signoff, ECO, and handoff workflows
Extend YAML/configuration systems to model workflow intent, stage contracts, validation markers, generated artifacts, override order, and backward-compatible project behavior
Improve Make, Perl, Tcl, Python, and related launch infrastructure for generated runsets, EDA tool setup, distributed execution, status tracking, and failure diagnosis
Build faster prelaunch and in-run checks for missing inputs, stale generated files, invalid hooks, broken environment setup, bad constraints, and inconsistent design state
Develop job-control and observability capabilities for hierarchical and internally launched workflows, including parent-child job attachment, logs, provenance, and structured status
Partner with design and CAD users to debug failures across EDA tools, Linux environments, shared filesystems, schedulers, generated collateral, and configuration layers
What We Need To See:
B.S. or M.S. in CS, EE, CE, or equivalent experience
12+ years building, modernizing, or operating production EDA, VLSI CAD, RTL-to-GDS, physical design, or large engineering workflow systems
Strong hands-on experience with RTL-to-GDS or implementation flows, including setup, generated collateral, tool launch, checks, timing/signoff handoff, and debug workflows
Strong Tcl and Make experience in real EDA automation environments, plus practical software engineering skill in Python, Perl, Go, or C++
Ability to reason about layered configuration, includes, overrides, variable expansion, generated outputs, validation state, and compatibility with older projects
Excellent Linux debugging fundamentals and a track record of improving legacy production systems without breaking active users
Ways To Stand Out From The Crowd:
Background with production flows using commercial synthesis, place-and-route, timing, extraction, DRC/LVS, power, or signoff tools
Experience designing workflow engines, runset generators, configuration systems, template-driven automation, or job-control infrastructure
Background with distributed schedulers and shared compute environments such as LSF, Slurm, Grid Engine, or similar systems
Experience with NFS-heavy shared filesystems, stale state, partial writes, generated input files, provenance tracking, and reproducibility issues
Experience building structured checks, validation markers, data-fidelity tracking, dependency tracing, observability, or better-tested legacy Tcl/Make/Perl replacements
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.
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 a diverse 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
- B.S. or M.S. in CS, EE, CE, or equivalent experience
- 12+ years building or operating production EDA, VLSI CAD, or large engineering workflow systems
- Strong hands-on experience with RTL-to-GDS or implementation flows
- Strong Tcl and Make experience in real EDA automation environments
- Excellent Linux debugging fundamentals
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.
-
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.
-
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.
-
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.”
