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Software R&D Engineer, Digital Logic Synthesis - New College Grad 2026

NVIDIANVIDIA·Semiconductors

Compensation

$116,000 - $218,500/year

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Posted

6 days

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About the role

NVIDIA's success builds on a foundation of industry leading hardware. A key strategy in achieving this is our combining of the best of external EDA with highly optimized, internal EDA tools. Our team develops these tools by fusing advances in parallel computing, machine learning, and novel algorithms in C++. We are seeking an innovative EDA Software R&D Engineer with particular interest in strategies and algorithms for RTL synthesis, digital logic, timing, and power optimization. Such optimization usually includes a mix of graph-based algorithms, AI, and feedback from RTL and physical designers, so having experience relevant to each of those areas would be ideal. In practice, techniques often depend on many related domains, so a solid understanding of DFT, clock distribution, power gating, and other SOC integration aspects is essential.

Developing software within a leading hardware company means getting to almost exclusively focus on the latest processes and most advanced designs. We're not bogged down by legacy support, niche roles, or convoluted approval processes. Our developers enjoy unusually high intellectual freedom and the ability to explore broad roles. If you like to work across many technical areas and see your successes directly realized in the world's best AI hardware, this is it!

What you’ll be doing:

  • 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 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.

What we need to see:

  • MS or PhD in Electrical Engineering or Computer Science (or equivalent experience).
  • Experience with EDA software and/or VLSI flows with focus 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).
  • Experience in EDA techniques, including logic synthesis, global route, static timing analysis, power & area optimization and SAT solvers.

Ways to stand out from the crowd:

  • Previous experience involving RTL logic synthesis and multi stage logic optimization is a plus.
  • 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 is widely considered to be one of the technology world’s most desirable employers, and due to outstanding advancements, our teams are rapidly growing. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology? If so, 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 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 19, 2026.

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.

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Aplyr's read

NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.

Synthesized from recent postings & public sources

What's promising

  • NVIDIA leads the GPU market, crucial for gaming and AI applications.
  • The company invests heavily in AI and deep learning, driving technological advancements.
  • NVIDIA's strong market position offers stability and growth opportunities for employees.

What to watch

  • High competition in the semiconductor industry can impact market share.
  • Rapid technological changes require constant adaptation and learning.
  • Intense workload and high expectations may affect work-life balance.

Why NVIDIA

  • NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
  • The company's AI research is at the forefront of deep learning innovation.
  • NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.

Aplyr’s read is generated by AI from public sources. Was it useful?

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About NVIDIA

NVDA$219.51-1.77%

NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.

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