Software R&D Engineer, RTL Optimization Tools

Nvidia

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Santa Clara, CAAustin, TX
Salary
$136,000–$218,500 / yr
Posted
92 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $187k
This role $177k
$125k most similar roles pay here $236k

This role pays less than 58% of similar roles. Most pay $160,862–$214,000 — the shaded band above. At the midpoint, this role pays about $177k versus about $187k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Software R&D Engineer, RTL Optimization Tools

As a Software R&D Engineer, RTL Optimization Tools, you will join a team developing internal EDA tools by fusing parallel computing, machine learning, and novel algorithms in C++. You will invent methods for parallel, graph-based RTL traversal and analysis while devising strategies to evaluate the impact of design changes on data path latency, power, and clocking. Your work involves exploring LLMs, GNNs, GANs, and Reinforcement Learning to automate RTL modifications and developing high-performance algorithms for clustering and logic synthesis. The role requires expertise in C++, Verilog, SystemVerilog, and EDA techniques like static timing analysis and SAT solvers. You will solve complex problems related to large-scale RTL quality, timing, and power optimization while navigating technical domains such as DFT, scan chain insertion, and power gating to improve hardware design productivity for advanced systems.

What you'll do

  • Invent new methods for parallel, graph-based RTL traversal, analysis, and manipulation.
  • Develop strategies to analyze the impact of RTL changes on data path latency, power, and DFT.
  • Explore LLMs, GNNs, GANs, and Reinforcement Learning to automatically suggest or implement RTL modifications.
  • Implement high-performance algorithms for clustering, min cost tree covering, and logic synthesis.
  • Develop C++ software to optimize large-scale RTL quality, timing, and power.
  • Drive the hardware design productivity roadmap by identifying and solving new optimization opportunities.
  • Work directly with design teams to facilitate the deployment of CAD tools and solutions.

What we're looking for

  • MS or PhD in Electrical Engineering, Computer Science, or equivalent experience.
  • 3+ years of relevant experience in CAD software and VLSI hardware design.
  • Demonstrated ability in C++ software development, specifically for graph traversal, pattern matching, and optimization algorithms.
  • Familiarity with RTL design using Verilog and SystemVerilog.
  • Knowledge of hardware design concerns including scan chain insertion, MBIST, clock/power distribution, and bus architectures.
  • Familiarity with EDA techniques such as logic synthesis, global route, static timing analysis, and SAT solvers.
  • Experience with machine learning techniques like LLMs, GNNs, GANs, and Reinforcement Learning for optimization or code generation.
  • Strong communication and interpersonal skills.

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