Full-Time

Senior Software R&D Engineer

Digital Logic Synthesis

Updated on 6/24/2026

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$168k - $264.5k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Austin, TX, USA + 1 more

More locations: Santa Clara, CA, USA

Hybrid

Hybrid role; some on-site days in Santa Clara, CA or Austin, TX required.

Category
Software Engineering (1)
Required Skills
Verilog
Data Structures & Algorithms
Machine Learning
C/C++
Requirements
  • MS or PhD in Electrical Engineering or Computer Science or equivalent experience
  • 6+ years experience in EDA software and/or VLSI flows, with significant work in logic synthesis or digital optimization.
  • Strong CS fundamentals and modern C++ experience (templates/STL, concurrency libraries, profiling and performance optimization, data structures, algorithms, performance, concurrency, testing).
  • Solid understanding of RTL (Verilog/SystemVerilog) and digital design concepts (timing, clocking, DFT basics, power intent).
  • Expertise in EDA techniques, including logic synthesis, global route, static timing analysis, power & area optimization and SAT solvers
  • Good communication and interpersonal skills
Responsibilities
  • Invent and develop new algorithms for RTL synthesis, digital logic optimization, graph-based RTL traversal, analysis, and manipulation.
  • Build physical-aware synthesis techniques using placement/congestion/timing feedback to improve PPA.
  • Develop strategies for rapidly analyzing the RTL change impact on timing, power, area, and impact to DFT, clocking, and power delivery on design.
  • Prototype and evaluate ML methods (e.g., GNNs, RL, models) to guide optimization decisions; integrate successful approaches into production.
  • Explore high performance algorithms for clustering, min cost tree covering (technology mapping), datapath implementation and other details of logic synthesis, especially that efficiently incorporate human insight.
  • As with any software engineering team, we do write a lot of code, but this is broader than a typical CAD or EDA role. Instead, we as a team own the whole process from discovery and invention of new optimization opportunities, to developing solutions and working directly inside design teams to facilitate deployment. That translates to a bigger picture view of your work, going beyond simply responding to user requests to instead actively driving the roadmap of increasing hardware design productivity.
Desired Qualifications
  • Previous work experience involving RTL logic synthesis and multi stage logic optimization
  • Experience with common EDA building blocks, such as Verific for Verilog parsing, Espresso for logic minimization, and various other components for logic rewriting, tree coverage, SAT solvers, and combinatorial optimization
  • Experience in high performance software design including multithreading, distributed computing, efficient memory and I/O use, etc.
  • Experience with various machine learning techniques.

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify's Take

What believers are saying

  • Blackwell and Rubin refreshes can drive another enterprise upgrade cycle.
  • Hyperscaler demand for AI infrastructure expands GPU, networking, and interconnect revenue.
  • Jetson, robotics, and edge AI broaden NVIDIA beyond data centers.

What critics are saying

  • Hyperscalers build custom accelerators, reducing dependence on NVIDIA GPUs.
  • China restrictions and domestic rivals like Huawei keep shrinking addressable demand.
  • Rubin execution slips open room for AMD and custom ASIC competitors.

What makes NVIDIA unique

  • CUDA and full-stack hardware-software integration create high switching costs.
  • Spectrum-X and NVLink Fusion extend control beyond GPUs into networking.
  • Annual architecture upgrades sustain first-mover advantage across AI, gaming, and robotics.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-3%

2 year growth

-3%
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